I'm going to go ahead and get started right on time. Thanks everybody for coming. This talk is called Machine Learning on Kubernetes, or Machine Learning Made Easy on Kubernetes. Basically, we're going to use Kubernetes and other open source projects to make machine learning easier. We could call that ML Ops. That seems to be the term that everyone's chosen. Apparently, if you put Ops on the end of anything, it clearly just makes it better. So now we're just doing that with everything. But I support it. I get the idea behind that. So let's get into it. First, my name is Brian Redmond. We got through the name part that my name is Redmond, and I work at Microsoft. I've been there about 18 years coming up on 19. I'm a part of the Azure Global Block Belt team. We basically help customers adopt open source solutions on our Azure Cloud. And that can be anything and everything in that area. I'm based out of Pittsburgh.  So anyway, I actually want to start with the demo. We're going to talk about what I'm here to talk about. But it might be fun to actually do a demo first. I like to do as many demos as I can in these kind of talks. Basically, Game of Thrones had ended recently. We're not going to debate here about the last season and what it meant. But sometimes you're watching the show, and this kind of character comes on the TV, and you're like, who is that guy? I mean, we don't even know what's going on. So I built an image classification model using TensorFlow to basically allow you to put a picture in of anything and have it come back and tell you who it is. And again, this is kind of a demo. And you guys can try this yourselves. If you go to this link, aka.ms slash thrones, you can try it. You can take a selfie. It'll tell you which character you are. Can't promise what you're going to get back. But I'll show you how it works here. So let's take a look. So this is what it looks like. Basically, it's just a web app. But it is talking to a trained TensorFlow model that's using TensorFlow Serving running in the cloud. Apparently, I need to end the show. Thank you. So basically, what we do is we select a photo. And in my case, if I were to pick that Benjen character, if we didn't really know who he was, it'll actually run that against the model and comes back and says, yep, that's Benjen Stark. I'm 98% sure. And we can run it again against something else. Like, for example, I could pick a picture of myself here from a trip I took in Denmark. And it's 82% sure. I'm Robert Baratheon, which is flattering. Also, spoiler alert, he's dead. So I got that going for me. So feel free to try that out. The demos I'm going to do later after I explain a few things are all based on, how did I build this? How did I train the model? How did I actually incorporate this into a pipeline and actually do this on a consistent basis? Again, the predictions are kind of a little bit bogus just for demo purposes. But you get the idea. So that's what we're dealing with. So let's start out by talking about what is machine learning. I would imagine most of you in the room know what machine learning is. I like to turn to maybe a scholar in this field, Arthur Samuel, to find it as the ability to learn without being explicitly programmed. When we do programming, we typically program the rules around a set of inputs. Machine learning, we give it a set of inputs and a set of outputs. And it tells us the rules. And that's actually the really interesting part around it. We actually get the rules back and actually then may not even know what rules we're looking for. If we're doing predictive analytics on financials, we know we're trying to predict maybe the future price of a stock. But in some cases, the data, we don't even know what trends we're looking for. Machine learning can come back and actually find the trends for us. So it's actually super powerful. There's some really interesting examples out there. These are four that I looked up. The first one around open AI basically created a machine learning program that can compose musical songs, pretty complex songs with multiple instruments, different every time. Really good songs, by the way, especially if you like classical. You can go try this out on Open AI's website. Really, really powerful that that's even possible. We've certainly seen Microsoft as well as other companies reach human parity around speech recognition. And so we're seeing that computers can recognize what's said in speech just as good as humans. Certainly self-driving cars are happening all over the place. I imagine we have a good way to go on figuring this out. That's a pretty complex behavior that the computer has to emulate. But people have made tremendous progress. There are some interesting examples, even all the way back to 2015 around self-driving cars. And certainly in the gaming world, we've seen the Google's example as well as a lot of other interesting examples using AI and machine learning around gaming to actually play games like a human would play. Very powerful stuff, lots of things that we can do with machine learning and AI. But what we found is it's fairly difficult. In general, training these models involves a pretty hefty amount of hardware. Some of these jobs may run for many, many hours, sometimes even days, to actually train a model and get a result out of it. We may have very large, complex data sets that we need to distribute across a bunch of machines to actually incorporate the training across those machines. Imagine that if we're doing machine learning on a cluster of, say, 10 machines, which is a very common exercise, how do we make sure that data's available to all of them? And suddenly we want to train it on our data center and then we want to trade it in a cloud provider's data center. How do we move that data around? How do we not have this cost of fortune for something like a GPU that does cost a hefty amount of money? So managing all of those resources and coming up with a plan around that is fairly difficult. We can turn to things like Kubernetes to help us. We hear a lot about Kubernetes. I think we all know what Kubernetes is. It's a container orchestration platform. It's certainly seen a huge amount of growth. And these are some of the reasons that came back from a study by the CNCF, why we saw that growth. Portability, scalability, and agility. And certainly those things apply to machine learning quite a bit. We want to be able to train in our data center, but I work with customers who their data center can't handle the training workloads that they're bringing to what they have. They want to be able to burst that training out into the cloud and bring it back. Kubernetes could allow them to do that. They can run Kubernetes in their data center and they can run it in the cloud and you frankly can run it anywhere. And certainly from a scalability standpoint, if we have a lot of CPU cores in the cloud or in our data center and we want to use them as effectively as possible, it would be nice to have some sort of scheduler and orchestration platform to take care of that for us. And certainly being able to do things like that that we do in DevOps in machine learning, I think ends up giving us a greater sense of agility around that. So we think about machine learning and what we need in a platform. A lot of people really think about building the model. If you look at TensorFlow and you start to learn TensorFlow, a lot of it is about building deep learning models, structuring a model, and maybe even training that model. But anybody who's worked with this knows that there's quite a bit more to it when you're doing machine learning. And this is just some of the typical steps that you'd go through to build and really use one of these models. There's a whole lot of effort around the data. The data is probably the most important part. You're gonna get data from wherever the sources are that you have it. You've gotta bring it in, maybe even do some level of analysis and transformation around that. The data may be coming in in various formats. It may not be prepared for the type of model that you're building. You have to have validation data as well. This is actually one of the biggest mistakes I think people make with machine learning is their model looks really good based on the validation set that they had. And maybe the validation set looks a lot like the training set. Well, then of course it would work out. In this Game of Thrones demo I've done here, that's exactly what I've done. I've trained the data against a set of pictures. I don't really have enough pictures to build something super interesting so it tends to work against the pictures that I started with. But we really have to have a better way to validate these models so that the results that we're getting that we trust are actually accurate. Certainly we wanna maybe do things like training at scale and then take that model and roll it out. And in the bottom part of this picture, it probably looks a little bit more like traditional CICD around web applications. We've got some model. We now need to deploy it maybe as a container to a set of a web platform of some kind and make it available to our web applications, our customers, some sort of public API, whatever it is that we're building. And so this is kind of what I would consider a typical machine learning workflow. We need a better way to do this to make it easier. Well, the Kubernetes community at KubeCon 2017, which at this point is at least a year and a half ago, introduced an open source project called Kubeflow. And Kubeflow's charter really effectively was to make it easy for everyone to develop, deploy, and manage portable distributed machine learning on Kubernetes. So entirely Kubernetes-based have a platform that adds that extra layer on top of Kubernetes orchestration that actually is focused on machine learning. It did, the Kubeflow name effectively started out around TensorFlow and Kubernetes. It's expanded well beyond that. The idea kind of, if you think about it this way, you have all these different environments. You have a cloud environment. Maybe you have a training environment in your data center. You have some experimentation desktop type environment. You can run Kubernetes across all of those. So I can get this consistent layer of orchestration no matter where I'm running. And then for that machine learning workflow, I can use Kubeflow. And then I can bring, because I have Kubernetes everywhere, I can easily bring Kubeflow across those and do all those same things that I wanna do around machine learning in a consistent way. I get these layers of abstraction in the same way that Kubernetes helped me abstract my applications and programs as containers from the hardware. I get Kubeflow to abstract my machine learning activity from the Kubernetes infrastructure. And in the long run, we really want people, like data scientists working on their code to not really be thinking about pods, Kubernetes deployments. We want them to be focused on the machine learning, but yet take advantage of what they can get out of something like Kubernetes. So effectively what they get, maybe we call it MLOps, cloud native ML. I'm not too caught up in what we call it, but I certainly wanna see some of those kind of benefits to make this easier. And I do think Kubeflow is a great platform for this. There are other open-source solutions out there for these kinds of things. I'll focus kind of the rest of this talk on Kubeflow. What do you get out of Kubeflow? It won't go through all these features kind of one by one. It, again, started as just something centered around TensorFlow. They started layering any other kinds of platforms like PyTorch, MXNet, layered in tooling for things like serving. I mentioned TensorFlow serving, but someone might wanna use Selden for their model serving. That's a platform or project that you can use. They're basically trying to bring in various other projects and make it a complete package that's integrated and easily managed to deliver these things. They added a pipeline feature, which I'm gonna show you in a demo here to basically give you an ability to actually create a pipeline that runs this entire workflow or that picture we saw earlier, let you orchestrate what that pipeline looks like and automate that and allow all those steps to actually run in your Kubernetes cluster. The pipelines that I mentioned, that one thing I wanna spend a little time on before I go into some of the demos, you can imagine if you have a few steps that run in some sort of order, we could write some big Python or Bash script that would run and execute all of these for us, but we don't really know that each of these run in the same language. It may be really difficult to cram all of that into one place. And we also need to pass information between each step. It would be great if we had some kind of pipeline system that would help us coordinate all of that. If we had just a simple way to write or script this kind of workflow and allow something to execute it for us. So that's what Kubeflow Pipelines are about. To me, this is really one of the best sort of solutions that they've added into Kubeflow. This idea that I can create this complex workflow with lots of different sort of paths through how things occur and I'm not writing a bunch of if, then logic and code. I'm really just saying, here's the order of the tasks that I'm working on and then containerize each of the steps as we go so that Kubernetes can end up executing all of this in the background. And that's the advantage of Kubernetes that sort of gets a little bit hidden in this picture, but all of these different activities we're doing and some of the things you'll see in the demo, they all get submitted to Kubernetes and execute. And Kubernetes is handling all the scheduling. I don't really have to think about, do I have resources available? I could turn on auto scaling in my cluster and ensure I always had resources at the right time as I executed all of these steps as I go. So again, that's the sort of high level picture. I actually think it's better to see some of this stuff in action. And so we're gonna do a little bit of a demo using this Game of Thrones web app. Again, there's the link if you wanna try it out. But basically we're gonna build the model using a TensorFlow application. We're gonna train it using this concept of a TF job in Kubernetes. We're gonna serve that. We're gonna do something around what we call hyperparameter optimization. And then I'll show you kind of the pipelines and even something like Jupyter assuming we have time. So, sound good? Any questions before I cut over to that? Okay, cool. Well hopefully you can see everything here. What I'm gonna start with is actually the code. So this project is actually, it's out on GitHub so it is actually out on that demo app. You'll be able to go out to GitHub and find this. But basically the training program, it's called Retrain. It's actually one of the TensorFlow samples. And the reason it's called Retrain is it takes the inception image classification model and retrains it against a set of pictures that I have here. So you can see basically for each of those characters I have a set of pictures that essentially labels them as, I know these pictures are accurately these people. And this program just basically turns through those and says, okay, if anything looks like these, I'll know that I'm gonna use that as the model and train that. The training program gets into a Docker container and basically I'm just using the TensorFlow based image. It can be done with a GPU or not a GPU. And I run this Retrain script with Python. And I'm a big fan of containers so if I were to do this locally I would run this as a container more than likely. But certainly if I'm gonna bring this to Kubernetes I need it as a container image. I'm gonna store it in some container image repository. Now I could just run that as a Kubernetes job but the place where Kubeflow comes in is they add these custom resource definitions. Kubernetes supports an ability to expand upon the default API and add your own custom resources. In this case there's this concept of a TF job. So in my case I only have a single worker so this is pretty straightforward. But TensorFlow jobs can look a lot different than this. I could have one parameter server and a series of workers, a distributed TensorFlow job that's running. It's nice to be able to define those here as one object or one TF job and let Kubernetes take over and execute that for me. It would be a lot more effort for me to spawn all these distributed jobs and manage it myself. I can just specify this as this resource. And effectively here's the container image that I'm using. Again it's stored in this case in our Azure container registry. I pass in a series of arguments and parameters. This is where I would specify if I wanted a GPU in this case if I wanted to do that. So let's actually go run one of these in my cluster. And by the way down here in the cluster you can see this is everything that's running. I've just got a kind of a watch of the pods and services. So I've run some of these things before. This is the web app that you guys are hitting when you're trying this out. If we take a look at TF jobs in my cluster you can see I don't have any actually at the moment. So we're gonna go and deploy one of these. I've got a little cheat sheet here so I don't have to type these. So as soon as I add that TF job first of all you'll see that we now have a TF job. It did if you noticed not at the bottom it actually spawned a worker down here. And that's this one here. And we can actually take a look at the logs. You can start to see the beginning activities that it's doing. It actually goes and downloads the inception model and goes and it'll start to work against the data that I've passed in. Now if you think about this you might be looking at this and thinking data scientists this looks a little tedious.  And effectively we don't. I mean that doesn't sound like that's gonna help them progress forward. It actually sounds like it's gonna set them back. And really the goal is for them to be able to actually write the Python code and push that to some sort of get repository and let this kind of stuff actually happen and some sort of CI CD style automation and kick this thing off. And that's the way a picture that's happening but we're just kinda walking through it here at this interface. What Kubeflow also gives you is a dashboard as you might imagine. So if we come to the Kubeflow dashboard that's running in this cluster and we click on TF jobs we'll see all the TF jobs that are running in my cluster. In my case I only have this one that we just spawned here. It tells me it's currently running. I can take a look at the logs and see what's actually happening. And so someone could interact with this and actually manage everything probably in a little bit more of an effective way without learning Kubernetes. I could actually come here and manage jobs that I'm working with without really learning any of the YAML or any of the Kube CTL commands and things like that that Kubernetes requires. And so that's super helpful. What ends up happening here is once this is complete over in my case in Azure I'm using Azure storage to store all the output from this so that I can actually use it later. So for example, in this storage account I have I have a file share and basically the output is training summaries in latest model. So when I ran this earlier I ended up with the training summaries which is used in a tensor board so I can see the logs and the accuracy around the training that I ran. And then the latest model is where I've stored the model so that it can be used with TensorFlow serving. So that effectively when that training is done I don't need that container anymore. The output that I cared about is now in the cloud stored in storage and I can spawn other containers that can mount that and use it. And that's what we'll do later in this environment. But you can see what one of these tensor boards look like. This is standard TensorFlow stuff but we get one of these outputs here that shows us kind of the accuracy for training and validation that we see. This is what they typically should look like though in some ways this model is not very interesting.  So that's what the tensor board looks like. The next stage that we would want to do now that we have a trained model I'm not going to wait for that sample we ran to finish. Now that we have a trained model we want to serve this thing. And what this will look like in our YAML for serving is a standard Kubernetes service and deployment. The service handles the networking aspect and then the deployment is actually the container itself. And so for this deployment I basically used the standard TensorFlow serving container image. I pulled that from the TensorFlow repository. And notice here in my volume mount without knowing a ton about how we do Kubernetes volumes and storage and so forth I'm mounting that latest model folder. So that's going to take the model that we build out of training and mount it into TensorFlow serving and provide it as an API endpoint. And TensorFlow serving basically provides that wrapper so that I now have an API that I can talk to. And let's try that out, see what that looks like. And in my cluster here you can see I do have that serving running and the service is running at this IP address on ports 8500 and 8501. So TensorFlow serving actually supports HTTP and GRPC for those playing along at home. So basically if I do a curl against that I've got this picture of Daenerys Targaryen I've encoded it as a JSON object because this actually requires that. But it's just basically a simple curl call here against that. I'll get back a payload that actually tells me what the model's prediction is. This is exactly the same endpoint that the web app is hitting if you're trying out the web app. And notice the fourth one down it's 0.94 that's essentially 94% sure that this is the actual character that I've submitted. And again I did submit Daenerys Targaryen if we look the fourth one down that's actually the one that it predicted. Which of course is what we expect. And so when we tie these things together with TensorFlow serving and test it out that's how we're able to actually deliver this web application that we tried earlier. And we can pick another photo. I think it's kind of fun to pick Drogon if you're a Game of Thrones fan, the dragon. If we do an image classification here we do Drogon, notice we get back it doesn't know that it's Drogon but it picked Daenerys Targaryen. And as we know most kids look like their parents. So in that case it's actually fairly accurate. So I like that. So the next thing that's important to note is when we ran these models there's a series of parameters that drive the training exercise. The learning rate, the optimization model we use the number of steps or iterations through the training that we run. We call those hyperparameters in machine learning. And so what you often have to do is pick the right hyperparameters to get the right result. And what I found is when I first started working with machine learning I thought that there was a lot of science to picking these hyperparameters. I thought that there was people that really understood the math and they just thought .01 is the learning rate and they did a bunch of scribbles. And what I found was they're frankly just guessing. They really are. They're guessing at what these hyperparameters are and just trying it out. And it's a bit shocking to me but that's actually how it works. So what ends up happening is if we have a lot of different hyperparameters we end up having to run a lot of different combinations. Imagine if we have three different parameters every time we try maybe a combinations of 10 we could be running hundreds of various trainings using a lot of resources to get the best result. And so what we end up doing is we can sort of provide better ways to optimize the right result from that. Now the way I did it here is I used something called Helm. Helm is a way to package up jobs that we submit to Kubernetes and provide parameters for them. And it's a good fit for something like hyperparameter optimization. What I have here is my two hyperparameters for this training that we ran are learning rate and training batch size. And I've given it three possibilities for each. And so what this will do is it'll go out if we looked at the underlying Helm chart which isn't worth learning here today it would go out and run all the combinations of these. For those doing the math at home how many is that? How many do we end up with? Nine, yep. So we end up with nine different containers. And again if I'm gonna submit this to Kubernetes and allow it to run these nine containers it's sure great that I don't have to think about what nodes have what resources available where can I find resources for these? And potentially see them all running at once and decide to kill a few of them because they're not really leading to the right kind of results that we want. And so this actually helps me do this. And again underneath the covers my TF job looks like this.  The other thing that I'm doing here it's kind of interesting is I'm using this thing called the virtual kubelet. So in my cluster over here if you saw I had a number of different pods that are running but if we take a look at my cluster and the number of nodes I have I actually have five nodes and this thing called a virtual node. The five nodes actually represent virtual machines so I'm paying for them all the time. Whenever they're running I pay that my cloud provider in this case Microsoft Azure to run those. But when I'm spawning these hyper parameters do I really want to spin up? Maybe I need nine nodes to run that. Do I really want to scale this out to nine nodes and then pay for them and then maybe I forget and leave them running or things like that. So the virtual node is not a virtual machine at all it's truly a virtual node it's actually just software. And if I submit things to the virtual node in this case it'll spawn them as what we call container instances in the cloud. And they actually will just be containers in the cloud and I only pay for them while they run.  But the key is in this node selector again if you're not too deeply familiar with Kubernetes doesn't matter too much but we said we wanted the nodes that are labeled virtual kubelet and that's what represents that virtual node and that's what really drives and controls this. And so when I do this helm install here I basically say install this chart use the values that I gave. I've got a crumb under my return key if you have a Mac you know how that feels. So what this is gonna do is again go spawn all of those pods for me into the cluster it'll take it a few seconds or so to kick off but instead of assigning those to one of the nodes in my cluster it's gonna put them on the virtual node and they'll all go run as container instances. And then I can actually again still capture all that data into my cloud storage and actually look at things like the tensor board and figure out which of the values actually was the right result and actually decide and then use those going forward. And actually I'll show you the tensor board here while we're waiting for those to start because it looks a bit crazy. I don't know if this is the best way to decide the result because it looks a little bit too hard to follow but you can see all of those different jobs are run and I can start to narrow it down and know which ones map to which values and so forth. So you can see them all starting here. You can see some of them kicking off and creating if we go over to the container instances view here you can see a few of them have actually kicked off and started. The beauty of this again is while these are running I'll pay for them as soon as they stop as soon as they're done I stop paying for them. It seems perfect for machine learning and that's kind of the idea around this. If I have a big Kubernetes cluster and I'm willing to pay for those VMs and if it's a good fit then great and do it that way and we have that choice and flexibility. The other thing that I think is interesting and perhaps in the long run a better way to do this is something called Catib. So again, projects that have been added to Kubeflow this actually came out of some work done by Google to essentially do this exact thing. Let's figure out a better way to optimize hyper parameters for a training exercise and let's take the same one that we're looking at here. In this case I've added an additional hyper parameter the number of training steps and basically we give it a feasible space or a range of options for each of those parameters. So you can see for learning rate I've said it's either between 0.001 and 1.0 training batch size, learning steps. I've given it a big range and it's actually gonna go out and start to spawn all kinds of pods with combinations of these. But then it's actually gonna use its own learning to come back with some validation and try to figure out on its own the right output. Now that's actually super powerful because we're effectively using machine learning to figure out the right set of outputs and optimize them. And this is pretty powerful technology. I don't entirely have this working for real so that's what it would look like if you set it up but the random example actually shows it pretty well if you take a look at the study. This is just kind of like the hello world for Catib but I think this is pretty interesting. It basically comes back with the bunch of workers that it spawned and you can see accuracy and validation accuracy come back for each one. So each one of these workers was a Kubernetes pod with a container running in it and so it spawned all of those and actually tried to analyze that and come back with the right result. And again, Kubernetes is taking care of where do I have the resources available? I could use the virtual node here if I wanted or it could actually spawn them and run them and orchestrate all that for me but as a machine learning data scientist this is actually what I care about and I'll be able to pick at the end if validation accuracy is most important then apparently this set of hyper parameters is the right choice and so that's pretty cool. All right, next thing I wanna show you is pipelines. So again, this training actually Game of Thrones has a bit more steps to it than just kind of training the model and serving it and so it could look like something like this. We could pre-process the data, maybe adapt some of the image files into some format that my model can understand. I run some kind of training against it like we ran, I can score the model and then in my case I'm just for the sake of the demo I'm converting the model into a couple of formats that can be used for different kinds of purposes and so I've converted it to TF Lite and Onyx maybe for using it in some mobile or lightweight environments and then I've got a step that copies it some other place and whatever your pipeline steps would look like you actually can go in and define them and the way that you define them is actually in code. This could look a bit daunting for the first time but basically Kubeflow Pipelines uses a Python based definition language and it's fairly simple. I mean effectively each of these steps you define a container image, a set of arguments and you give it a name and so this is essentially container operation and then the steps you can say things like after the previous step run this one and effectively allows you to create whatever workflow you want. You can add logic here to say if this output happens do this but you do it in a language that's a little bit more discernible it's just based on spawning these different kind of steps. We can do things like define the input parameters that we want, the storage characteristics that we need for each of the container images. We basically upload this into Kubeflow Pipelines and we end up with exactly this picture and then when we execute them they end up looking like this. And so you can see they're all green because they all ran. If we take a look at training for example and clicked on logs we see all of that output from that training exercise. We see that it ran in this case 2,500 learning steps. I came out with some level of accuracy and maybe have some scoring exercise that tells me my average accuracy for this model. Whatever those steps are for you you can plug that in here and customize a Kubeflow Pipeline to get what you need. And so this is fairly powerful we can easily run one of these it's actually so simple to do. We give it a run name. We pick which pipeline we're gonna run. You can create different experiments which effectively groupings of different exercises that you're running. And this is where I provide the number of steps. Maybe I wanna do 5,000 this time and I wanna do a learning rate of .01 and I click start and off it'll go. And again these will actually show up over in Kubernetes as containers. And actually if we really wanna see them they'll actually end up in the Kubeflow namespace. You'll actually see kind of all these steps running. And somewhere in there for that one that we just kicked off one of them will appear here and start and each of those steps will run. And again Kubernetes is orchestrating all of that for us. Super powerful. The last thing I wanna show you before we wrap up is the notebooks. So not the notebook, the romantic movie of course that we all know and love. Jupyter notebooks really drive quite a bit of our work in machine learning. Before we really get to the point where we're ready to orchestrate end to end pipeline and process we really need to experiment and iterate on what we're building. And a lot of that work is typically done in Jupyter notebooks and that's a pretty familiar term to most people. But actually creating environments for a lot of people to use Jupyter notebooks starts to become a bit cumbersome. They maybe do need a GPU and they only need that notebook for a short period of time. And so we provide this notebook platform in Kubeflow where someone can first of all come in and say I want a new server, they pick whatever image they want and these can be custom images that the administrator defines, the memory in CPU, storage and so forth and they spawn one of these and then they'll get a notebook which actually will look just like this previous screen. But in the background, again it's running as a container in Kubernetes. So then I can say connect and as the data scientist I get this familiar interface and I can go in and do some sort of additional fun Game of Thrones analytics around this particular one which I pulled off of open source somewhere that someone did, they basically are trying to analyze which family had the most success in all the different battles because this is what people do with machine learning and all their free time. But this is actually pretty fascinating, the amount of analytics these people have done around Game of Thrones battles and so forth. But again, if someone needs a Jupyter notebook to do this kind of work, pretty simple to request one and make it available and get to work on it. And that's kind of the idea behind Kubeflow's implementation of notebooks. So that's it from a demo standpoint. I am gonna take a couple of questions. I'll kind of wrap up with that. We have at least a few minutes and I don't remember if it's lunch or not. But I see a question in the back, ask it away. So the question is, I did this in Azure, could you do this on any cloud? Absolutely, the place that you have to customize, maybe a couple of places you have to customize, the main place is storage. So that's the area in this that varies from cloud to cloud, whether it's private cloud or a public cloud like Azure. So you have to adapt that part of it. But in that pipeline, you saw a part where I kind of defined that in code. I can actually make that parameters of that program and make it pretty easy to say, run this one here, run this one here. The other thing is I stored my container images in the cloud, that's probably not a big deal. There's container repositories everywhere. But I said at the beginning early on, one of the huge benefits of Kubeflow and Kubernetes is that portability cloud to cloud? I wouldn't call it cut and paste magic, I just pick it up and run it here. But the amount of time to adapt it from cloud to cloud is fairly small. Question here. You're not supposed to catch details like that. No, he asked basically, in the first training example, the images were stored in the container and then later they weren't. Yeah, that's very observant. Some of these things are things that you do in a demo when you're doing them up in front of people and you only have 25 or whatever minutes. If you copy them across from remote storage, it's not very efficient. It may actually make sense to store data super close to your container. There's probably a lot of other ways to make that efficient. From a demo point of view, you can imagine the things that you do. It probably doesn't make sense to store all the data in the container. It makes the container super big. And so that's not really the way you would do it, but it's certainly good for demo purposes. But yeah, good question. Back here. Yeah, I guess the question is, can you do that parameter optimization in notebook? Yeah, I mean the notebook gives you the ability to do kind of anything you want. Now in this example, the way the notebook works is I have a Jupyter notebook, that's my container. So it actually runs my notebook in a container. And I can do a lot of different parameter optimizations within that, but if I actually want to spawn a bunch of them in parallel, then I probably can't spawn that from my own single notebook. I probably don't have that power as a user. And so that's where it might be interesting to try these other methods. And that kateeb is an interesting idea. It would still have someone need some knowledge of kateeb. The reason my Game of Thrones model isn't quite ready to do that yet is I need to provide the output in the right format for kateeb to pick it up and decide was it good or not. But yeah, people could certainly manually run a bunch of examples and come to the right idea. And that's probably what they do early on before they come to the cloud and test out the final set of good guesses. The feasible space they might determine on their own. One more question, and then I think I have to get out. But I couldn't hear. So the question's about ETL and adding steps around bringing in data. I think that's a fair characterization of the question. Yeah, absolutely. In fact, Kubeflow, I mean, you can certainly do things manually, just importing data, but Kubeflow does provide ways to use common tools that people use for this kind of thing, like Pachyderm is an open source project and a tool that people use for data manipulation, ingestion, all kinds of powerful capabilities around Pachyderm. But they help you deploy Pachyderm in your Kubernetes cluster and take advantage of it for steps like that. There's probably a bunch of other ways you might do ETL around machine learning data, and you can incorporate those steps into either the pipeline or use tools that you get. The idea is if something's not there and you want to use an open source project, Kubeflow is open source, so bring it to that project. But so far, they've done a pretty good job bringing in most of the common tools. It's at release .6. I was actually using version .5 in my demo here. It's not at release version one, but version .6 actually came out. So they're getting there pretty quickly on Kubeflow. So again, I'll take questions as we wrap up. I think we might have another speaker or not, but I appreciate everybody's attention. I hope it was a good, valuable talk, and thanks a lot. Enjoy the rest of the talk. Thank you.


Like the first thing that got me excited about this book was The dedication that Nasim has done for the book, right? And this is the dedication and this is the notes that I took. It's not sort of copied down Because I didn't want to track down the Twitter info that Nasim had given regarding this dedication, right? But basically the dedication is this He's dedicated the book to two men of courage. The first one is Ron Paul And he calls him a Roman among Greeks. Okay, and I had to look that up and I'm gonna explain to you what Roman among Greeks says Okay And the other person that is dedicated this to is Ralph Nader And He referenced he he calls him a Greco-Fanishian saint, right? Got the love it got the love it Okay, as far as Ron Paul goes What he called Ron Paul was a Roman among Greeks, right? and Didn't understand what he was referring to I thought about it I know a little you know a little bit of my Roman history a little bit of my Greek history And all that jazz and I couldn't figure out what in the world this meant, right? So I did a little looking up and I found Twitter Post tweets Nasim had done. Okay, so I'm just gonna read Nasim's tweets a couple of tweets that he did, right? The real difference in politics isn't the right versus left graduation, but rather Greek versus Roman, right? And this is what he says Greek is what Greek means Greek equals puts theory about practice Roman equals puts practice above theory, right? So Greek puts theory above practice Roman puts practice above theory. So when he goes along and calls Roman among Greeks He's saying that Ron Paul is putting practice above theory Where a lot of these bureaucrats and politicians lobbyists and all these while lobbyists, I'm pretty sure they know what the game is about, right? But these politicians and these people in centralized power, they're Greeks, they're academics, they're theories, right? Ron Paul is saying What's working in practice, right? And he continues on he mentions a couple more things The Romans judged their political system by asking not whether it made sense But whether it worked, right? And this one he's Declare-minded Tom Holland. He was quoting Tom Holland, right? And I looked up Tom Holland was but we leave that alone, right? Which is why I am and then he continues, Nasim, which is why I am calling Ron Paul or Roman among Greeks upon on the dedication of the black swan to Benot Mandelbot, right? So he did, I guess I don't have black swan, but I guess he did a dedication to Mandelbot The person who came up with fractals and mathematics, right? Fantastic, right? Which is a pun On the dedication he made in black swan for Mandelbot calling, I'm assuming he called Mandelbot a Greek among Romans, right? Which is super cool. Which is super cool Okay So that's the dedication page. That's where Nasim is coming from. Okay


Sure. I don't know if they're my posts or people from the website's posts, but absolutely, yeah. First one, one of the most viral videos of you on the internet is the day that... Ah, popcorn kid. This was fun because, like, look at everybody else's face there. They're all looking backwards, and so I see him, he's got this, like, that kid, right? He's like my son Preston's age at the time, I think. Everybody's kind of looking back, right? And looking for the ball, it's like five or six rows deep. And I see him with this big barrel of popcorn, and I'm like, hey, can I have some of that? And he just kind of looked at me. Right. And so I snagged him. Did you ever end up meeting this kid after?  Oh, okay. That play was, like, during these days, I feel like you probably would have gotten some sort of popcorn sponsorship or something like that. Yeah, who knows, right? I've seen guys nowadays, I see them, like, I think I've seen Prince Fielders snatched some nachos. Never once have I seen somebody doing it, so it's cool. But, yeah, I don't know, I probably wasn't the first, but it was fun. Now, so you take a look at that post, and now you look at now. You're the one giving the fans some stuff. Here you are giving the young fans some gum. This guy, not every day, but there's another kid that's like in the box seats there. And when he comes, Jonathan, every day he's there that kind of makes him the gum. So it's kind of become a ritual every day to give him gum. It's still awesome that you always give back and you also kind of take notice to people who are on the stands. I remember one time you were coming through New York and there was a young girl who had a son saying that she was named after you. And you went on over, hopped over the bench and the railing and took a picture of things. Right. I've actually met a number of kids recently that's been named Mattingly. And it's always cool, it's always humbling for me, honestly, because someone named her kid after you. It's like pretty special, really. But usually it's in the past, early on it was like a dog or a cat or something. But I've got a few kids now. That's humans. And I love the girls, little girls too, because we don't have any. Six boys in our little blended family, right? So it's always good to get a little girl, I feel like it's mine. Now here's a boy right there, which these sons, now this is at Marlins Park, so they're following you everywhere. Whether it's New York, Miami. Yeah, it is. It's like Milwaukee, there's a kid in Philly. It's cool. I love it, honestly. I really do. Again, like I said, it's always humbling and an honor to me when someone does that. Now when we talk about iconic photos. Yeah, the hit name. This is what everybody remembers from you too. Yeah, I know. This is amazing. Great poster. It had to be the spring of 85. In that time, at that funny, if you look at that right knee, I had a scope. I had torn meniscus and I had surgery right before I came to spring training.  And I remember, I'd been out for probably a couple of weeks, I was rehabbing. And I remember as we were shooting this, Mr. Strymbiner walked by.  And especially if you weren't like, number one, I'm hurt. And I can't get on the field, but I'm doing this kind of stuff. Right? And you're always like, oh man, he's like this. So it ended up being cool. Yeah, I was going to say, I'm sure once he saw it, he was probably like, you know what? That was really sweet. You probably hated it first, but over time he probably was okay with it. How about this one? Got the mullet going? Yeah, mullet. A little slow?  Those were the days, right? Mullet days. Looks like you're ready to match a couple of baseballs. I don't know. I was shocked when I seen that, how long that was back there. That was really long. Way longer than I looked. Way worse than I thought it looked. I thought it looked really great. Right? But it looked awful. Will you ever grow back? The mullet? No way. No chance. You have to get it back. The hair's going away. And less, not more. Love to be able to have that much. Here's the nice moment it looked like. Yeah, I don't know. I look at that, I'm just looking young. You feel like, man, I was so young. You should enjoy this game. Look, I'm having some fun, right? Yeah. So I think this game is meant to be played with some fun and joy. And that's what you grew up with, right?  You loved baseball. At least I did. And I think the guys that play at the best have the most fun. And it seems like they're having fun out there. Now, in a lot of these photos that we just looked at, you're obviously having fun. A lot of your baseball cards, you have some awesome ones. And one of the best ways that you've been able to raise money is by having people donate towards signed autographed cards. So who do you have a favorite photo of yours that you have taken that you've seen on a baseball card, specifically the off top of your head? You know, like if I had to say my favorite baseball card, it's probably my first one. Obviously, your rookie card.  And you see these guys in the big leagues and your dream is to get to the big leagues. And I shouldn't, I wouldn't say I dream to be in the big leagues and have a baseball card, but I mean, that's kind of like, when you see your first baseball card, it's almost like, wow, that's a dream. So the top's card is the first one ever. Got to see. And I was like, that's kind of the one I think about the most. Obviously there's been a lot since then, different companies and sets and, you know, all kinds of different cards that you see, people I think make some of them. But yeah, your first one is really like the one you think about. Cool, love it, love it. All right, so talking a lot about iconic photos and this one right here, here you are, with Derek Jeter, captain of captain. Yeah, I have no idea what I'm telling him there. I probably didn't need to tell him anything. Let's try to stay out of his way. You want me to give you what I think about when I think about that photo? Yeah, why not? Yeah, look at that.  I'm like, God, probably like 220 or 215 there. I was like, dude. You still got it, though. You got the nice mustache, too. You had to get rid of that, too. It's turning white. It's like, get rid of the mustache. So this was a pivotal period in your look. I'd imagine it changed after this. It did, quickly. The mustache had to go and had to lose some weight. If I would have seen that photo, I would, yeah, whatever. No, I know exactly who you're talking about. Think the same thing? Yeah. All right, so then fast forward. Here you guys are still together. It was pretty cool. Yeah, I'm happy about that. It's really cool. Seeing Derek from the standpoint of his first spring training, coming to camp, looking like total misfit, right? Like didn't fit in. Just wasn't. You know, you've seen major of the guys. You see a kick him out of high school. It's obviously not fair. But then thinking about the changes over the next spring and then the next spring. And then really what he was able to accomplish. And then now he owns a club and an executive and leader of our organization. And it's cool to be a part of this and what he's doing. Honestly, he's doing a great job. And I think bringing the same mindset as he has a player to what we're trying to accomplish now, the consistency of staying with the plan and all the things that he talked about when he originally came in. I think they're going to pay huge dividends over time. Now something that's amazing with you that you've been able to do has been able to keep so many great relationships, closer relationships. Teach people what you know and you have so much wisdom whether it's on the baseball field or off the baseball field. And a lot of that you get to pass down to whether it's Jeter who we're just talking about or guys like John Carlos Stanton. Yeah, John Carlos was obviously here a couple of years and seeing him from the other side of the field with Dodgers, just a tremendous player and talent. And kind of watching him play was exciting. Obviously the second year he had there was off the charts and kind of he struggled early. It seemed like in the year before he kind of was struggling. Found it then, ended up having a pretty good year but this one he stayed healthy all year long. And any time this guy stays healthy, it's going to be a monster here. Now right here on the golf course. That was at the golf alley at the beginning of spring. So I bet he hits it a long way. That's what I would think. And you swing lefty on the golf course? I do. Awesome. Is it as sweet as your baseball swing? Probably, I don't know. I don't know. Whatever it is, it's not producing any good results. That's what I'll say about my golf game. I don't play that much but it's not turning into scoring. That's what I would say. I may have a good swing but I didn't get any hits. You can say that got a great swing but you never hit. Alright so we're coming down to home stretch and a lot of what you learned has come from some great people who you've played with and been associated with. You are the boss, George Stambrader, Buck Showalter. Yeah I've seen that photo. I like that photo. You know the boss was always relaxed in spring. He was always having fun. And you know just Buck coming in was I think a pivotal moment. Within the Yankee organization.  And I thought when Buck came in he set the course. He did a nice job of him and I think it was stick. It was a GM at the time. I thought they did a great job of bringing in the right players and changing the tone of the rocker room from guys that just didn't, partially guys that didn't care. And brought in gamers and guys that played hard and it mattered to them if they won or lost. And I think that was, I look at that as a turning point in the Yankee organization for me at the end of my career but also the organization moving forward after that. Based on what you said before I'd imagine that this is the look that you really like. Got the short hair, nicely freshed mustache and looking lean. I don't know, yeah younger right? I don't know if I ever like mini photos I see of myself but it is younger. Alright here's another great photo of you guys here at Ted Williams' Wadebox. Man what were you guys talking about and where were you? This looks awesome. I think this is Teo Peppies or something like that. It's a little place to cross from Mr. Strymer's hotel. It was in spring training. I think sports illustrated article with Peter Gammons and we were talking about weight shift and weight and Ted pretty much ran the conversation and we just talked hitting and it was fun. And it's really been an article that a lot of people have referenced and talked to me about. They seen the photo and we had a lot of shrimp and beer and that was a good night. That was the best part. And being around Ted really was an experience. Obviously Bogsy, we weren't teammates at that time. We were on opposite sides but it was cool to be there. Ted was great. Yeah, very thankful for that right there. That's a pretty cool time. Amazing photo, definitely a frame type photo. We're going to end with this one. A road back photo of you. How old were you? No, I was 17, 16, 17. Yeah, high school. I don't know when to what year I was in state championship when I was a junior and we lost in the final game as a senior. So we'd won 59. I think about that. I think about we won 59 straight games, had a chance to win back-to-back state titles and we got beaten in the final game. What would you say is your favorite part about social media from what you know? It's always fun like Lori posts a lot of Louis and what's going on and just getting videos from her. I'm not quite sure all the stuff that she posts but whatever she posts and she's sending me too I know I get to see it. So I think and then hearing feedback oh I follow Lori and Louis, I see him so cute and stuff like that and so I love that interaction of it. I think the other part I like is just our foundation being able to show what we're doing with kids and how we're affecting lives. If it's through computer labs or it's through reading programs, it's through sports. I think the fact that it's a good feeling to see these kids' faces and I love seeing what we're not only being a part of what we're doing but then being able to see it and then see it's kind of good because it's almost like a record of what you're sometimes you're doing something and you're getting a computer lab together one year and then maybe you're doing a reading program in another year but then all of a sudden four or five years down the road you get to see kind of like all of it and it's like you know we're making some headway and we're having a positive effect in our community so being able to see it through that is always good. So now's the time for the plug which is what does Mattingly Charities Instagram and Twitter page have to offer and why should they follow you guys? Well, I think the biggest thing is if you're interested in Mattingly Charities I mean it's not so much I'm not much on the personal side of it myself but I see the value but I think more than anything if you want to follow what's going on and what's happening in probably our community or I guess if you're interested in what I'm doing there's a reason to follow and see really what we stand for I guess that's what it really does I think our charity really represents our love for kids and our belief in that we've got to help the most underserved kids and give them a chance to have to make good decisions to give them an opportunity to have success that I've had or anyone has had and let them know that it comes through education it comes through making good choices for kids but you've got to have those opportunities to make good choices and some kids don't get the same opportunity I think is almost always there the choices are just so much harder for certain kids Awesome, hey well Don thank you so much for letting us catch up with you talk a little bit about some of your fun posts and now you know where to find this guy Madeline Charities, shoot him a follow a lot of good stuff on the way, right? Cool, always doing more


But today we're in chapter 21. We're gonna look at verses 29 through 33 here in the gospel of Luke as we continue our study in this gospel. And so let's begin reading together here in Luke chapter 21 at verse 29. I'll read to verse 33 and we'll get into our study. Luke chapter 21, beginning at verse 29. Luke writes, then he spoke to them a parable. Look at the fig tree and all the trees. When they are already budding, you see and know for yourselves that summer is now near. So you also, when you see these things happening, know that the kingdom of God is near. Assuredly I say to you, this generation will by no means pass away till all things take place. Heaven and earth will pass away, but my words will by no means pass away. Now as we begin chapter 21, remember with me as we've been looking through this chapter, Jesus had prophesied that the Jewish temple would be destroyed. In verse five of chapter 21, we read then as some spoke of the temple, how it was adorned with beautiful stones and donations, he said these things which you see, the things will come, the days will come in which not one stone shall be left upon another that shall not be thrown down. So Jesus had prophesied that the Jewish temple would be destroyed. And as he had done that, it prompted a question from his apostles, that question is located in verse seven, when they asked him, saying, teacher, but when will these things be, and what sign will there be when these things are about to take place? And so the entire chapter of 21 actually is Jesus's answer to that one question. And so as we've gone through chapter one together, throughout this chapter, Jesus has been giving various signs concerning his return. He had spoken concerning the fact that there would be a period of general troubles that would occur throughout the entire church age, but that there was also a specific time that is referred to by Jesus as a time of tribulation and great tribulation that would occur also at the very end. As a matter of fact, there is going to be a seven year tribulation that begins with increasing judgments occurring in the first three and a half years and then the great tribulation would ensue from that point concluding with Jesus's return. And so Jesus has been speaking concerning these things and answered to the question that had been asked of him. Now he has made it very clear that what we call the second coming, the second coming is going to be as real as his first coming. And the reality of that, and this is I think where the rubber meets the road, the reality of that is if we really believe that Jesus is true to his word, if we really believe that, well the reality of that would be that my life would be lived in such a way that it reflects that I believe that. A lot of times my theology and my behavior don't really jive, they don't really go together. My beliefs and my behaviors sometimes are entirely different. I really do believe that it's possible for us to believe all the right things about the return of Christ and still be unsaved or still be very carnal. And so when we study the word of God many times as it relates to the return of Christ there's an exhortation that's attached to his return. I'll give you an example, it's found in 1 John in chapter three, verses two and three. In that passage when the apostle John was writing, 1 John three, verses two and three, he said beloved, now we are children of God and what we will be has not yet been made known. But we know that when he appears, we shall be like him for we shall see him as he is. Everyone who has this hope in him purifies himself just as he is pure. Everyone who has this hope in him purifies himself even as Jesus himself is pure. In other words the return of Christ is an incentive for living a godly life. When we really believe that Jesus is returning then we live as if we anticipate that return, and it makes sense to me, if I really think that he's returning I'm gonna live as if he's going to come. It makes perfect sense. In Titus chapter two verses 12 through 14 the apostle Paul said God's grace is teaching us that denying ungodliness and worldly lusts we should live soberly, righteously and godly in the present age. Looking for the blessed hope and glorious appearing of our great God and savior Jesus Christ who gave himself for us that he might redeem us from every lawless deed and purify for himself his own special people zealous for good works. Recently when we had a prayer meeting here related to the proposition eight and all and as we gathered on Friday some of you were with us on that Friday night and we shared various Jack Hibbs and Raul and I shared that night here in that prayer meeting. I shared a little bit with those who were in attendance and I said it's an interesting thing that we Christians are very vocal saying that we need to preserve traditional marriage. When there are statistics, the disturbing statistics that you can find with the study that George Barnett did I think it was in the year 2002 in which it was demonstrated that evangelical Christians have a higher divorce rates than atheists and agnostics. And as I said that people it's hard to believe isn't it? I mean people who actually say I believe in traditional marriage aren't keeping their marriages together and atheists and agnostics are keeping their marriages together and so I was sharing listen if we're gonna have an impact in the society it's gonna be the impact of character. It's gonna be that we have actually learned that God's commands are truly holy and just and therefore we ought to keep them because of all people on the face of the earth we believers are the ones who love the Lord and fear him the most I would think and that's the whole point. So when the Lord Jesus Christ is teaching his disciples concerning his return well there's a motivation that ought to cause me to be anticipating that and that's the sense that when he returns I'm gonna be as he is and therefore if I have that hope in me I'll purify myself even as he is pure I'm gonna live a life that is holy it's gonna be zealous for good works and that's what the proper understanding and study of last days is supposed to produce it's supposed to produce a people who are expecting Jesus to return and living every day as if he is. It was asked of us one time in a meeting that I was in and I've repeated this in my own studies because it spoke so much to my own heart that the question was asked if you knew for a fact beyond a shadow of a doubt that Jesus was going to return and there's no doubt about it he is gonna return and you knew the exact time it's gonna be next week at a certain time if you actually knew that the question was asked exactly what is it that you would do different in your life is there anything that you would do differently if you knew beyond a shadow of a doubt that within one week Jesus is returning and that question was posed of us and so naturally I begin to think what would I do and then the next statement is then you need to start doing that now because that's how you really demonstrate that you expect that the Lord is really returning but if we're saying well the Lord delays his return then in essence what I am is I'm not really believing that he is gonna come back so the hope of his coming ought to cause something in me, something called a zeal for holiness that actually changes my life and so not only do I have proper doctrine but also I'm doing the things that I believe not only do I have proper beliefs but I actually have behavior that accompanies my beliefs and so that's what it's all about and that's what Jesus is speaking about and so Jesus is speaking concerning his return and here in this passage before us he gives a parable it's called the parable of the fig tree so he's illustrating his answer by using a fig tree and so notice what he says in verse nine he's verse 29 rather he says he spoke to them a parable look at the fig tree and all the trees well as he begins to speak here he's saying listen the signs that I have been speaking about well when these signs begin to occur and my coming is very near and this particular parable is prophetic because it is speaking specifically to the generation in existence just before his return and he says you to look at now and notice this the fig tree and he actually speaks of the fig tree and makes mention of other trees but look at the fig tree is what he says and as he uses the fig tree we need to understand that in scripture Israel is often represented by a fig tree very often in the Old Testament for example in the book of Deuteronomy in the Old Testament the fifth book of the Bible in Deuteronomy chapter eight verses seven and eight we read the Lord your God is bringing you into a good land a land with streams and pools of water with springs flowing in the valleys and hills a land with wheat and barley vines and fig trees pomegranates, olive oil and honey and so fig trees is part of what represents the nation of Israel in Hosea in chapter nine verse 10 we read I saw your fathers as the first fruits on the fig tree in its first season so in the Old Testament the nation of Israel is often represented as a fig tree when Jesus was speaking in the gospel of Luke he would use a fig tree on occasion to represent the nation of Israel for example in Luke chapter 13 verses six through nine we saw this already but Luke writes he told this parable a man had a fig tree planted in his vineyard and he went to look for fruit on it but did not find any so I said to the man who took care of the vineyard for three years now I've been coming to look for fruit on this fig tree and haven't found any cut it down why should it use up the soil? Sir the man replied leave it alone for one more year and I'll dig around it and fertilize it if it bears fruit next year fine if not then cut it down and we saw that as Jesus was giving that parable he was speaking concerning the unbelief of the nation of Israel a nation that was rejecting its Messiah and was not producing fruit of righteousness now when Jesus was ministering Matthew records this Jesus actually at the end of his ministry cursed a barren fig tree in Matthew 21 verse 19 Matthew records seeing a fig tree by the road he went up to it but found nothing on it except leaves then he said to it may you never bear fruit again and immediately the tree withered so we know that that tree symbolized national Israel a spiritually dead nation the Israel had an impressive outer appearance of religion but in reality produced no fruit it was dead and so that's what Paul would say concerning that nation when he wrote in Romans chapter 10 verses one and two brothers my heart's desire and prayer to God for the Israelite is that they may be saved I can testify about them that they are zealous for God but their zeal is not based on knowledge they're not producing any fruit and so when Jesus here in Luke chapter 21 verse 29 speaks of the fig tree we know that as he gives this parable he's speaking concerning the nation of Israel in verse 30 he says when they are already budding you see and know for yourselves that summer is now near so he's saying they are already budding the question has to be asked what does that mean what do you speak about Jesus when you say when you see that they are already budding well perhaps what he's referring to or alluding to would be the nation of Israel and in a prophetic sense the miraculous rebirth of the Jewish nation now all of us obviously are aware of the fact that Israel was scattered around the world for over 1900 years but it miraculously once again came to exist in 1948 and so that in and of itself is a miracle but I wanna show you something in the Old Testament book of Ezekiel turn with me please to Ezekiel chapter 37 and I wanna show you something found in the Old Testament book of Ezekiel Ezekiel chapter 37 this is a nation that miraculously came back to life I've shared this with you so often all of you are very familiar with this read your Old Testament and look at all the different peoples there Philistines, Jebusites, the Canaanites, the Parasites all the ites there's so many ites uptight, sadisticites, cellulites I like that that's lots of ites Israelites but try and find those people groups now look for them and they're not here they don't exist of course they're out of existence now but we have the Israelites we have the Jewish nation that's a miracle in and of itself scattered throughout the world and yet brought back into one nation in 1948 well this is an answer to a prophecy that we find in the book of Ezekiel in chapter 37 now we'll look at verses one through 14 here because what this records for us is a vision called the vision of the valley of dry bones now just so that you know Ezekiel this book was written 586 years before Christ 586 BC and this chapter here the verses that we're gonna be looking at especially the first 14 verses this chapter has had over time various interpretations there are those who look at Ezekiel 37 one through 14 and view it as presenting what would be called a general picture of resurrection from the dead there are others who would say that this passage speaks only of Israel's regathering from Babylonian captivity and being brought back into the land of Israel it's a picture they would say of the nation awakening to life once again in the land of Israel but it relates to the regathering from the Babylonian captivity there are others who would say that this is simply a picture of a political revival of the nation of Israel but in reality what this is showing to us is the spiritual condition of Israel during the centuries of its dispersion it also points to the national resurrection and restoration of Israel to the land now how do we know that well before we read verses one through 14 notice verses 21 and 22 because it reveals that to us it says Ezekiel 37 21 and 22 then say to them thus says the Lord God surely I will take the children of Israel from among the nations wherever they have gone and will gather them from every side and bring them into their own land and I will make them one nation in the land on the mountains of Israel and one king shall be king over them all they shall no longer be two nations nor shall they ever be divided into two kingdoms again so this is quite obvious a picture of the national resurrection and restoration of Israel to the land that took place in 1948 but let's read verses one through 14 together and I'll give you some insight into this as we're considering the parable of the fig tree beginning at verse one Ezekiel 37 the hand of the Lord came upon me and brought me out in the spirit of the Lord and set me down in the midst of the valley and it was full of bones and he caused me to pass by them all around and behold there were very many in the open valley and indeed they were very dry he said to me son of man can these bones live so I answered oh Lord God you know again he said to me prophesy to these bones and say to them oh dry bones hear the word of the Lord thus says the Lord God to these bones surely I will cause breath to enter into you and you shall live I will put sinews on you and bring flesh upon you cover you with skin and put breath in you you shall live then you shall know that I am the Lord so I prophesied as I was commanded and as I prophesied there was a noise suddenly a rattling and the bones came together bone to bone indeed as I look the sinews and the flesh came upon them and the skin covered them over but there was no breath in them also he said to me prophesy to the breath prophesy son of man and say to the breath thus says the Lord God come from the forewinds oh breath and breathe on these slain that they may live so I prophesied as he commanded me and breath came into them and they lived and stood upon their feet and exceedingly great army then he said to me son of man these bones are the whole house of Israel they indeed say our bones are dry our hope is lost we ourselves are cut off therefore prophesy and say to them thus says the Lord God behold oh my people I will open your graves and cause you to come up from your graves and bring you into the land of Israel then you shall know that I am the Lord when I have opened your graves oh my people and brought you up from your graves I will put my spirit in you you shall live and I will place you in your own land then you shall know that I the Lord have spoken it and performed it says the Lord so this chapter is called the prophecy of the dry bones we see in verses one and two that Ezekiel's been brought out in the spirit and set down in a valley full of dry bones these are bones that are sun bleached it's obvious that they have been there for some time and as he looks at it there is absolutely no life physical nor spiritual that he can see and so as he's looking at this notice verse three God asks the question son of man can these bones live and so that emphasizes the impossibility and hopelessness of the situation can these bones live?  Well what's the answer? Well as far as I'm concerned absolutely not and that's why Ezekiel answers in the way that he does he says oh Lord you know this is beyond my ability to answer it requires more power than man possesses to make these bones live is what he's saying and so he's looking at a valley of dry bones it's absolute death there's no life whether physical or spiritual and God asks that question can they live? Only you know God it's beyond my power so he says prophesies verse four prophesy to these bones say to them oh dry bones hear the word of the Lord thus says the Lord God to these bones surely I will cause breath to enter into you you shall live I will put sin use on you and bring flesh upon you cover you with skin put breath in you you shall live then you shall know that I am the Lord so the life giving word of God is going to accomplish that impossible task the life giving word of God he said prophesy because it's a word of God that brings life to that which has no life Jesus said the words that I speak to you they are spirit and they are life that's how you and that's how I got saved we got saved because we heard the word of God we got saved because somebody proclaimed a message that had life in it we embraced that message called the gospel and as a result of that we were regenerated we were reborn we who were walking dead people zombies if you will we who were spiritually dead became alive because of the life giving word and so here as Ezekiel is prophesying and speaking he's basically being told that the word of God is gonna give life to this nation I am gonna restore this nation I am the one he's saying who will do this even though it's an impossible task he's saying I will bring life to these dead bones the nation of Israel will once again come to life and ultimately what will happen is they're gonna recognize that God is their Lord and so Ezekiel obeys him I prophesied verse seven as I was commanded and as I prophesied there was a noise and suddenly a rattling and the bones came together bone to bone indeed as I looked the sinews and the flesh came upon them and the skin covered them over but there was no breath in them also he said to me prophesied to the breath prophesied son of man say to the breath thus says the Lord God come from the forewinds O breath breathe on these slain that they may live so I prophesied as he commanded me and breath came into them and they lived and stood upon their feet an exceedingly great army this is a picture a picture of Israel now the result here as he prophesied over these bones is that they once again are clothed with flesh but I want you to see it but they're still dead that would be a picture of the nation of Israel reassembled but without spiritual life which is the way it is right now I mean sometimes when we go to Israel we have people who are first time first time they go to Israel who are so excited because they're going to go to what is called the holy land at least there are those who call it the holy land but once they get there they discover it's no holier than any place else and they enter there and they find that the majority of Jewish people who are living there today the majority overwhelmingly are agnostic non-practicing the Jewish religion doesn't really matter that much to them outside of some of the the holy festival days and all of that but they don't live overwhelmingly they don't live under the law they're not living as believers for some it's actually a great disappointment when they see that the nation has been reassembled and in a miraculous fashion it has come back together bone to bone if you will the flesh has been put on this but there is no spiritual life the life has not yet to come it reminds me of how that when God took the ground as it's recorded in Genesis and he took the ground and he formed the dirt into Adam into man and it shows that in the original creation of man the picture there is of God working in a very tender way producing the first human being but the Bible tells us that he was just laying there until God breathed into him the breath of life the nation of Israel is a nation that's been reassembled as we have seen it since 1948 but it has no spiritual breath within it it hasn't come to a knowledge of its savior Jesus Christ it's a beautiful nation it's beautiful but it's without life and it will not have life until the spirit of God enters in and that's what we see now that's what we have now the first stage of God's work in Israel the nation continues to slowly regather but the nation has no life in it no spiritual life and that's what's taking place here and that's why ultimately God is gonna breathe life into this nation you see after the tribulation we've already looked at how the Lord is gonna bring that nation through and he's gonna refine that nation after the tribulation God once again will be their God that's what's being referred to in verses 11 through 14 here in Ezekiel when it says, son of man these bones are the whole house of Israel they indeed say our bones are dry our hope is lost we ourselves are cut off therefore prophesy and say to them thus says the Lord God behold all my people I will open your graves cause you to come up from your graves bring you into the land of Israel then you shall know that I am the Lord when I've opened your graves O my people and brought you up from your graves I will put my spirit in you you shall live I will place you in your own land then you shall know that I the Lord have spoken it and performed it says the Lord that is what's gonna take place just prior to the return of the Lord Jesus Christ when the tribulation concludes and those have come through the refining fire and have been brought to faith in their Messiah and that's how that's gonna take place and so what we have right now in the nation of Israel and you can turn on back to Luke chapter 21 what we have right now in the nation of Israel is it is being reassembled it continues to be reassembled even as I speak now but ultimately it will be the nation that once again God is it's God at this moment that is not true with that nation and so back in chapter 21 at verse 31 Jesus says so you also when you see these things happening know that the kingdom of God is near so when the nation of Israel regathered and once again became a nation that should have been for believers a sign that Jesus' return is approaching you know if you like to study the Bible and you go and you buy commentaries and some in this church like to do that and you buy commentaries and all and you're doing last day's studies you might find this interesting if you buy commentaries that were written in the 1800s, 1700s you know earlier commentators and all there's some very rich things to learn from some of the early church fathers as they left some of their material behind and all for us but you read some of that material as it relates to the nation of Israel and you will see overwhelmingly in the 1800s, early 1900s overwhelmingly that when the commentators are referring to things that relate to the nation of Israel in the last days prior to the return of Christ they overwhelmingly practice something that is called replacement theology some of you have heard that term replacement theology what simply means that the church has replaced the nation of Israel in the plans of God and they do not see the nation of Israel as a literal nation any longer but they spiritualize it and so things that related to the nation of Israel are now ascribed to the church and you'll see that in the commentators and the reason is because some of these early commentators actually traveled to Israel and they would see that it was abandoned that there were basically nomadic shepherds Arabs who lived there there weren't many Jews who were there in the nation and all and in their mind it would be impossible to see this nation under control of national Israel once again and it didn't even have the name Israel anymore I mean to this day you can pick up books and you can be reading on Israel and what's the word that they use they use the word Palestine and the reason they use the word Palestine is because the word Palestine is really a transliteration of the word Philistine and what they're trying to call Israel is the nation of the Philistines they don't even want you to associate Israel with its own nation and so that's why even in some of my Bibles I will have the land of Palestine early commentators speak of the land of Palestine but in reality it's the nation of Israel and they couldn't believe they didn't believe such a thing could happen they didn't believe that this nation would one day regather and actually exist and yet what happened is in 1948 the miracle of miracles happened and the nation once again formed even as Ezekiel 37 made it very clear what happened one of the strongest arguments for the truthfulness of the Bible is the simple existence of the nation of Israel that's one of the strongest arguments you have when people say how do you know the word of God is true how do you know that Bible is true well Jesus spoke concerning the nation of Israel he spoke concerning it in this condition during just before he returns and over 1900 years it was abandoned there was no such thing as Israel it was filled with swamps when you're in Israel and you're in the northern portion of Israel and we travel up the highway there on the western coast and you'll be looking at all of these crops and they have various trees that they plant and it's become the bread basket if you will of Europe in many ways it produced a lot of oranges and citrus and various other things, avocados and all when you're going through that land your guide will point out to you that the land that you're driving through right now and all of these fields that you see at one time all of this especially in an area called the Hula Valley all things the Hula Valley the first Hawaiian lived there in the Hula Valley but when you're going through that they will point out that this actually this area here was swamp and what you'll see is eucalyptus trees they have eucalyptus growths everywhere and he says you know why you see so many eucalyptus trees he said they're not really indigenous to Israel actually they came from Australia do you know why there are so many eucalyptus trees up here in the Hula Valley and so naturally you're supposed to say no tell me oh great one why well the answer is because the eucalyptus thrives on a lot of water so they threw all these groves in there so it could suck up the water from the swamps and that's how they were able to drain those swamps and pull out all of that excess water through all these groves of eucalyptus trees and so they will tell you when you go into that land when you originally went in the early 1900s and oh this was abandoned all of this was there were no trees this is just swamp land as a matter of fact malaria was a very very destructive disease many people died of malaria but because the Jews went in and began to plant plants like that eucalyptus and all it changed the entire fabric of that nation so when you go into the nation of Israel to this day and you see it existing that's the sign Jesus was giving and he said when you see this fig tree beginning to blossom you know that summer is now you know that my return is near this was not specifically spoken to his apostles living at that time this is written for us in the end days to awaken us to the reality of the fact that Jesus' return is any day now now he says in verse 32 assuredly I say to you this generation will by no means pass away till all things take place heaven and earth will pass away but my words will by no means pass away now when he says I say to you this generation will by no means pass away till all these things take place that word generation is a word that many people argue over that word generation is a word that can be used at least two different ways the word generation one the word generation can speak of natural descent the successive members of a genealogy it would be speaking of a nation of people and so that would be saying this nation this Jewish nation as a people will not cease existing so this generation will by no means pass away is another way of saying that Israel will continue and will not pass away as a people Jeremiah 31 verse 35 says it like this this is what the Lord says he who appoints the sun to shine by day who decrees the moon and stars to shine by night who stirs up the seas so that its waves roar the Lord almighty is his name only if these decrees vanish from my sight declares the Lord will the descendants of Israel ever cease to be a nation before me if the sun stops shining in the day and if the moon stops reflecting its light at night only then would Israel ever cease to exist is what he's saying here and obviously the sun and the moon continue to do what they do but it also speaks of the people the people who are alive during the time or the end times who will be viewing these things and so I'm not somebody who runs around putting dates and I'm not doing that right now what I am saying is we have seen the nation of Israel regathered I believe that that's ample proof that the Lord's return is coming at least from his own word is coming soon and that generation, that nation of Israel continues to exist, it didn't cease to exist it continues to this day and I fully expect that he's gonna return any time now somebody recently asked me do you think the Antichrist is alive right now and my answer is I don't know I don't know he may be pastoring Calvary Golden Springs for all I know but I don't know for sure I wonder sometimes but the answer is no but see part of the reason well the answer is no is because it's obviously who knows but secondly as a Christian I'm not looking for Antichrist anyway I'm looking for Jesus Christ and so I realize he's returning any time and so what will happen is Israel is gonna become a nation which it did and that reveals that we're at the end of history but it also reveals that the rapture is about to occur the next event on the prophetic calendar and no other event occurs prior to this next event the next event on the prophetic calendar is the rapture of the church that's the next event that's the next thing that's gonna happen that fulfills prophecy is the rapture and that's gonna come it's gonna come soon and I look forward to that you know we used to say here we used to say I'll see you later and then the response would be here, there or in the air you know and that's kinda how we lived at that time when I first got saved I yes began to hear about Jesus' return first when I got saved at the age of 20 and yes it's been almost 38 years that I've been walking with the Lord and no he hasn't returned yet but that simply means that his return is one day closer every day I wait it's one day closer every day one day closer so again we ought to live as if we really anticipate that now finally when he says in verse 33 heaven and earth will pass away but my words will by no means pass away he's simply saying this he's saying the universe ultimately will be done away with it's gonna be recreated after the millennial reign of Jesus Christ you see that in the book of Revelation but God's word endures forever God's word is a sure word and it endures forever Psalm 100 verse five says the Lord is good His mercy is everlasting His truth endures to all generations Psalm 102 verses 25 through 27 in the beginning you laid the foundations of the earth and the heavens are the work of your hands they will perish but you remain they will all wear out like a garment like clothing you will change them they will be discarded but you remain the same and your years will never end 2 Peter 3 10 through 13 the day of the Lord will come as a thief the heavens will disappear with a roar the elements will be destroyed by fire the earth and everything in it will be laid bare since everything will be destroyed in this way what kind of people ought you to be you ought to live holy and godly lives as you look forward to the day of God and speed it's coming that day will bring about the destruction of the heavens by fire and the elements will melt in the heat but in keeping with his promise we're looking forward to a new heaven and a new earth the home of righteousness Peter said in 1 Peter 1 24 and 25 all flesh is as grass the glory of man as a flower of grass the grass withers the flower thereof falls away but the word of the Lord endures forever and this is a word that by the gospel is preached unto you heaven and earth will pass away but my word will never pass away it's the word of life and by embracing this word as you heard it as I heard it as the gospel was preached my life was transformed absolutely transformed uniquely made brand new by the life changing word of God it's through the embracing of God's word the living God's word the acting on God's word the obedience to God's word the trusting of God's word that our lives are absolutely transformed God does marvelous things marvelous things absolutely amazing things I was standing outside on Sunday and I was talking to a friend of mine we were talking about what God does how good God is and I said you know what all the Lord wants us to do is believe him just to trust him just to believe him and I want you to travel with me for just a moment in your mind's eye for just a second as I was speaking with him I was out there by the gazebo in your mind's eye you know where the gazebo is I was standing by the gazebo out there and as we were standing there I said to him I said turn around and look at the old building that we used to occupy I said you see that and he goes yeah I said if we didn't trust the Lord well one to be honest with you we'd have never even been in that building but if we didn't trust the Lord that's where we would be right now in that building I said do you see that patio cover there he goes yeah that wouldn't exist do you see that building right over here that children's wing there that wouldn't exist what that would be would be a red barn and three houses I said if you turn around and look at the sanctuary right now I said look at that that would be asphalt and dirt because that's all that existed here prior to this building I said everything you see on these grounds is an evidence of God working because we trust him to do that everything that you see is the hand of God everything and so I believe Lord I believe God can do abundantly above all that we ask or think I know that he can I have no doubt that he can but where did I learn that I learned that from the word of God and when you study that word and hold fast to that word God honors his word and that's why Jesus makes it very clear to us listen when you see this take place you know that summer is nigh my return is soon and what do we say? even so come quickly Lord Jesus we await your return come quickly we want to be with you


Hey curl friends, I'm Bianca Renee and you're watching Bianca Renee Today and today I am going to show you how to get rid of those hard Crunchy curls. I mean, let's be honest it happens. Sometimes you put too much gel Sometimes use a product that just makes your hair really hard and crunchy but If I'm being completely honest, I Actually like the crunch. I know it might be kind of weird to you guys But I mean definitely comment below if you can relate to this. I Prefer using a gel first of all or any product that will give me a little bit of Crunch or hardness because that tells me that this is going to make my curls last all throughout the week You should not be washing your hair every day You should just be refreshing and in order to have a good refresh day You have to start with a really good foundation and the foundation is That hard crunchy curl now if you like your curls to be super soft fluffy That's fine, but I know for me somebody was very fine hair My hair is just gonna look really flat and in order for me to get this volume I need a little bit of hold to keep everybody up and lasting throughout the week So in this video, I'm gonna show you how easy it is to fix this problem So we're gonna go from these flat hard boring crunchy curls to this big volumized soft Define curls But before I do this, I need to make sure that we're committed in this relationship We need to take it to the next level so I need you to follow me on Twitter Instagram and snapchat at miss beyond grenade I am so close to 200,000 subscribers and very close to 50k on Instagram and as soon as I get there we're doing a giveaway So make sure you're following me here on YouTube and Instagram push that little bell so you're notified as soon as I Giveaway goes live now back to our regularly scheduled programming So right now. I currently have my favorite gel in my hair, which is the Dippity-Doo girls with curls jelly I've talked about this gel several times. I think it's safe to say that it's my favorite. It literally costs 499 at TJ max. I Know super random. This is like a really old-school brand actually like I guess our moms and grandmas actually use this stuff but it Works so well for my hair You can tell when a curl is hard when you could literally like lift it And it stands straight up, but this means that this curl knows exactly what it wants It's gonna look like this and it's going to hold this foundation all week long Now there's two different ways that you can make your hard curl soft again by using one of two things The first thing you could use is a set of hands You literally just crunch your curls and keep scrunching them and that'll break up the cast So you could just keep going like this and eventually your curls gonna get more volume And you're gonna get rid of all that crunch by just scrunching it away or You could use a diffuser. This is the diva dryer with the curly-co diffuser I have been using this diffuser on my diva dryer lately because I feel like it's just faster So this is what I use especially on my refresh days So I'm gonna show you how to use both at the same time I mean I'm going to use my diffuser and use my hands to scrunch and my curls are gonna look fabulous at the end Of this and I'll prove to you that the crunch is actually a good thing So does currently 325 and I'll show you exactly how long it takes me to diffuse Many of you guys ask me if diffusing is allowed in the no heat challenge And it is because I'm using a low fan speed low heat and only for five minutes That's part of the reason why I do wait for my hair to air dry about 85% Because then I can get the job done really quickly. So now look at my curls now. They are no longer crunchy I'm able to get some more volume I have beautiful definition and my diffuser didn't make my hair frizzy because of that hold I would not feel comfortable using my diffuser if my curls were one wet or just like Super mushy and almost too soft because I know that that soft curl can easily be blown away and create frizz Where if it has a little bit of crunch to it that diffuser is not going to mess up the curl pattern So now I'm gonna shake this out a little bit more show you guys my final steps how I get that final look I Do have bangs. I have to shake them to the front And if it's a good day, they'll just Act right if you find any more crunch you could just keep scrunching until you reach your current desired level of softness Look at that guys look at it Look at that definition. Of course, I'm not satisfied with my volume level. So I am gonna grab my pick And we're going to make this even bigger and guess what this is actually my day for hair I have not washed my hair in four days and it looks this fabulous Another way you can make sure that your curls don't get hard is by using a leave-in first So if you use any type of gel and just make sure hair like hard as a rock use a leave-in first and then apply the gel That'll soften out the gelness But as some of you may know I don't really use leave-in conditioners because it takes away from that crunch that I secretly desire But to each his own try it do what works for you and once you do I want you to come back and leave me a comment and let me know how it worked Do you use a leave-in before your gel? Do you scrunch away the cast? Do you use you diffuser leave all your tips and tricks down below as well? I would love to know and if you learned a thing or two from this video or just enjoyed it or me in general Make sure you give me a thumbs up and subscribe I post two new videos every week once on Friday and once on Sunday and we have to stay curl friends You've got to follow me on Twitter Instagram and snapchat at Ms. Bianca Renee. I hope to see you guys next time Thanks for watching Bianca Renee today