All right Glad that you're all here. So yeah, my talk is going to be about it when to use machine learning First something about myself the who am I I've studied method and statistics a research master and During that time I got really interested in machine learning. So even though I was focusing on statistics in my study I was really interested in artificial intelligence So I'm also an Intel AI innovator What I love is open source innovation and particularly human machine interaction So how can computers help empower people And Yeah, I want to thank jibes for enabling me to speak here today I'm a senior data scientist there. I've been working there for almost four years at 15 different companies Dibes itself has 35 data scientists and In my four years I've worked on Blockchain Social robots from which you can see the picture Natural language processing for example chatbots or Analyzing the news like reddit or Twitter and a lot of purely machine learning predictive and That kind of projects So usually I say something about the open source projects that I've done, but I want to keep them for the talk actually so I Don't know if anyone's familiar with the gardeners hype cycle It's an interesting one to follow because yeah, they're discussing which thing like where are things in the trends with tech and This is where you can find me so I like to do these kind of innovation topics and I also forget help and so yeah, you can already have a look there So today I Want to first try to explain what machine learning exactly is and I'm not from like formulas perspective But like just to get you give you an intuition so no formulas and Afterwards I will tell you when to use machine learning because it's not you shouldn't always use it like that's a spoiler Yeah, I'm sure that a lot of you already have ideas what it might be or have applied it, you know Clone some get-up code or and then just run some example code or maybe a bit further than that But yeah, I hope something of this will be inspiring to you So let's start with what it is So this is an example where we have like the simplest possible data it's kind of sociology data that was my ironically my my major So I guess Does anyone to guess what that what the numbers would be there or like what would we predict as people here? Yeah, I think that it's pretty clear to see immediately like that's that's what we would think and Well, so yeah That's that's indeed flag what I compute what you would like a computer also to predict right I mean we we have this intuition, but how I kind of computer learn that so You wanted basically you want to compute it to be able to generalize from the example So it would for example learn on the first three examples and we able to generalize to other examples that it hasn't seen before So in this example You you would train on the first three and you would hope that it can predict the other two right? So let's say this is your whole data set. You're going to split it up And then you would learn on one part and validate your model on the on the other part Next day I wanted to show you this also the example in Python code Let's see how the switching is going so I don't know who of you is familiar with scikit-learn But it's a it's a very good library which helps you develop machine learning models And it popularized the fit transform and fit predict So like as long as you're still kind of making a pipeline you're doing trans fit and transform So you learn how to apply like Like for example with the age and the income it's kind of a function that you're trying to learn, right? You have an argument someone's age, and then you try to predict the the income and scikit-learn, yeah, it's really good for this kind of like stuff where you want to train on some data and then Yeah So I don't know if it's readable. I guess I'll zoom in a bit So let's first then create some data This is usually how you name the variables so the X is what goes in and Why is what you want to predict? Sorry. All right. Thanks so Can you evaluate it? And so this is this is how the variable would look like And the y variable Looks correct, right? So now we make a model and the idea is that you fit it on the data So you want the first three examples you want to learn learn on that and then you can predict The rest so yeah, what you can see here is you're you're using the first three examples then you're predicting the last one So yeah, this is like a way to learn a linear Relationship but the interesting thing is that in machine learning there are a lot of different ways that you can have a model And this is the simplest variation where you know, like numerical data And you will basically any model will have some kind of special like features that it learns from parameters that that's the thing That you're trying to learn so Here you can see that the value is thousand which means if you multiply the age by a thousand you'll get income So actually the interesting thing is of course what would it do for numbers that it hasn't seen and in this case? It will yeah, if you say 70 it will predict 70,000 obviously Okay, so this was a numerical example now kind of an idea of like Decision trees which you can draw always like if if this then that then that and there's two things here Like this makes it so that you can have a non-linear kind of like transformations or predictions and In the end you're predicting your yes or no, that's like not on a miracle value. So that's also possible and Another example is first of those is is predicting spam. So hi, John. How are you? We would say that that's not spam and cling cling for free that that might be spam Unless your name is John, then probably also the first one is spam. Yeah, so Rather than like what could we use machine learning for rather than write a lot of if else statements? You can learn base logic based on the existing input output examples So the steps here are like find a problem do some pre-processing in our example. We didn't have to do any Find a model that works and then use this best model in production So now I want to bring your attention to the following The significance of machine learning. I don't know if you guys know fan diagrams But you know, this is this is how machine learning is, you know or or actually I think it's more like this like machine learning is just a small part in this right you Like you want to automate some process and machine learning can be part of that. So now it's time to go to the examples Yeah, so this is a library that I put online and I Wanted to explain to you how I came to this idea I had installed arts linux on my Mac book. I would not recommend that. It's like it's a horrible idea Yeah, I don't try it at home But at at night Programming at night. I've noticed that there's difference between the like between the colors So you have those that are trying to know, you know, it's it's dark So it will apply some like orangey filter. I never got used to that one But what I noticed was that the browser which is mostly white Was still really bright compared to when I looked at my editor, which was really black so I thought, you know, it would be cool to kind of take that into account and I Also thought like it would be cool if instead of having like a lot of configuration That it would be cool if if you would have actually no configuration at all and it and you would be able to still like Like Be able to do something about it. So Yeah, this is example data of the bright ML that it takes and Maybe it's fun to show it. I'm not really happy about switching because it's a bit slow, but So, yeah, that's a new version, right? They always get these these things so whenever I switch between a Screen can see that it applies new brightness like at the for example, the last one is 73 and Going back to I don't know if it's visible on this screen. I guess not Now it starts doing it Okay, well It's mostly designed for a laptop. So I only experienced here if it would work on external monitor, but The idea is that yeah, you need to collect features that can help you predict it and These are the ones that I've got so you see here the new brightness, that's like When I'm raising the the brightness on my computer it changes this value It's a file actually on your computer and that changes and Whenever a change is being made to that then it's being recorded and it records these kind of features. So my battery Power level which application am I I'm in but also that that pixel value that I wanted So that's like a value between 255 and zero, right? So the idea is I want to have a model that could potentially learn the difference between You know high values low values and Maybe the time is important, right? Maybe location and last one ambient light. That's like the sensor in your laptop That's also useful feature of course because yeah, that already does some kind of like are we in the dark or not? So I had a question like does anyone else have ideas like what you would want to use as input here Well, I guess I got quite some here, but yeah, you can I I Actually find out one more yesterday, which was when I was when I was boarding the plane and I couldn't charge my laptop anymore I know it has a bad battery because I'm running Arch Linux on a MacBook, which you shouldn't do so I would have only like like 45 minutes battery or something and Even though my battery was completely full I still did not want I was still wouldn't want my brightness to like You know be full but from the model's perspective, it's going to be like yeah, you know, no problem with battery. That's just You know, that's just too full brightness because it's day. So yeah It's a bit of contradictory example, right? And as a person you would be able to like you can learn it But it's not going to generalize because whenever I'm ever going to be again in that situation It's going to be so rare and this is one of the main problems with machine learning these kind of rare situations So Yeah, the main takeaway here actually I didn't mention it yet But the cool thing about it is I don't have to do anything other than just change the brightness like normal And over time I should just notice that I need to change it less and less right so that's that's really the cool part You don't have to do this whole process of collecting data and whatever, you know, I want to change it It will work for that time you you go to a different situation So it's zero conflict. Well, it's still personalized and I think that's really cool about it But the thing is still you have to think about like which features are available and which do I want to use? but hopefully, you know, this would allow people to create their own brightness setting without too much effort and Brings me to my next one Which is another library So it uses a Wi-Fi signal to detect where you are and Here we go. Let's do it here Europe Python Fintree, let's see if it works. So I have it here See it's in my bar. So my computer knows where it is and I Think it's cool because this one is using a smaller module that I've made Just to get like just to give an idea of How it works So it uses the scanner and you have like a lot of Wi-Fi Inputs like some ideas and how strong your signal is. So that's kind of how this one works is If you're sitting on your couch or you're being somewhere else in the house The computer could know the difference because this the signal strengths are going to be different between the different access points that you have and The interesting thing here again is that is that Don't take pictures when there's an anti-slip No problem So the cool thing here is when we look at this one is actually using it So I really like this idea of creating small models that you can then use in like other things And I think that that's just that's where we have to go with machine learning create small models That then can be reused in in other components because I do think that you know where I am is actually going to be a Factor in in how your brightness would want to be or I mean it can be predictive of it. So click ability ski and Well, one of the ideas is easier to learn from you have Observation then to have to say something if my signal strength is this much, you know, like I don't know one wants to do that Right, that's like really crazy So oops, yeah, so Yeah, so I've told you how to solve some kind of X to Y problems, right? some input to some numerical value or some like class and So you can only solve these kind of problems some X to Y problems It's a pretty pretty limited you would think but People have been very creative in posing their problems as X to Y problems actually so for example in computer vision And what would be any respectable presentation without a seemingly off-topic picture? So This is a this is an example of the image net data set It's something like they I think they noticed I think they were predicting dogs and they looked at which ones were wrongly predicted and then they saw this I mean, I think it's very it's hilarious Yeah, so but how does how would you use this in a model, right? How did I do it? well It's like different classes in this case is it a dog or is it not a dog zero or one one is a dog and On the other hand you have pixels and this is the crazy part You have for every image you have like 80 pixels by 80 pixels by three channels like red green blue and Like that is something like I think across like 19,000 or something data points So you have to imagine each of those is a value between zero and 255 it makes it that you immediately have big data with some sizable number of images But yeah, that's so that's an idea of on computer vision and so I want to also talk about one one case at you know from work I've worked for multiple insurance companies and In one of them we wanted to investigate what computer vision could do for them And in this case they wanted to predict the amount of damage like how much it would cost to repair it from damaged car pictures and Well, it took a really long time to get this data because obviously they have not prepared for it to be used like this So we started working with a academic car data And so pretty much yeah, like this is an easy one But they have examples where you have like a tiny scratch and it's very difficult to see like the very small feature on the whole thing So we started with we also we actually made it a bit easier this problem for ourselves Like more on on like sides of the car like this as a start So we were trying to predict which side of the car we're looking at and then you would yeah So it's kind of about localization and I did this over two years ago But yeah, it's a good case because it's you know, it's very time-consuming in a way And so but the problem is is they don't didn't have enough data, you know, and The cool thing is though There's something called transfer learning where you're you can use like an existing model We at that time we used the inception v2 model from from Google. They were training it for like three months on like 30,000 euro machinery something like that and the idea is that they they made this whole network And only actually this like last red one on the completely on the right is the actual prediction is happening like you know This is a this is and in that case they use the image net. So it's like this is a dog This is a car. This is you know, a lot of like I think a thousand different classes But the cool thing is the part before that very last one that can still be reused in other cases So in our cases so features that are useful to help the dogs might not be that useful But you know, there's always some kind of features that it will learn to represent this whole date to learn this whole data set that you can use in another task and Yeah, it was it was a very interesting project it was when TensorFlow was 0.8 and We we made or we used their template to create an Android app We changed it so it would accept our model and so it's still fun to to walk around and Projected on cars and have a laugh every now and then Yeah, so what is typical in an insurance company is like they have strict strict rules already in place So that yeah, this was innovation. So that's that's one part there transfer learning can certainly help But you know like image data. It's it's a very difficult one. And I think I missed this point earlier We advised them not to continue on this one because it was not their core business this car Like that was just one of their things like we're very broad insurance company And we advised against you know going forward with this because it's just not their main like their cool thing And it would be very expensive to get to label all their data and and like that so and Another thing is like, you know, we are going to have a difficult one with with like compliance where you're going to be like You know 60% of the time it's a it's accurate like compliance doesn't really like that so I Wanted to go to another complex problem. I don't want to go too depth too much into depth in this one But I thought it would be fun to have a neural network learn to complete neural network code so so yeah There's a lot of generative models out there So you just give it a bunch of text and it will learn to predict the next word or character based on the things that I've just seen before so there's a generative model and That can be very generic it can be times the time data or it can be like text or or image images even But I don't want to go too much into depth about this one I Think that gender generating in company is not that interesting usually Unless you're making really that to be your thing like for example, I think is amazing What kind of art they make like Google made something called deep dreaming or something. It's it's very interesting art But yeah, so these are just like inspirational ideas. It's not really wouldn't really recommend Like this as your next project though. It can be interesting, of course So next one. I don't know who here has cryptocurrency at the moment. Okay everyone sold it off already Yeah, so This is actually my only personal closed-source code And Actually three years ago. I was working on the blockchain and at those times. I was also a bit skeptical of it I'm still quite skeptical of blockchain But yeah, I was always laughing when companies were were saying something like Yeah, we're combining AI IoT and blockchain and this is going to be the thing You know, like like now you have like three problems instead of like one Yeah, so But yeah, and those things are also I didn't have a lot of money And I thought it was also going to be way too expensive to trade these things like thinking about stock where you know It doesn't make any sense unless you have really big volumes And that I was already way too many people doing it But Actually a few months ago. I thought, you know, let's just collect data and let's analyze some of it and You know, most of the models Like the popular ones then they applied and latest machine learning techniques hoping that it's you know, it's going to give them an edge So basically what they're just doing is take this like price data over time And they hope that they're able to predict like if it's going up or it's going down It's what most people are doing I Thought I wanted to do it for for some time, but I thought, you know, yeah, that's not that's not really Like that's really risky or you know, I don't have anything to say about I cannot control anything is it's going to be You're going to wake up and anything can happen So, yeah, I thought, you know what I'm going to analyze the data I'm going to see like what are the most obvious things Like I noticed at one moment that a coin was like one of the coins was going to work together with With with Microsoft and that's really increased the price enormously So I thought, you know what if I'm just going to monitor for such events those things that, you know It's going to be obvious for everyone that the price is going up, you know that maybe I can do something with that So it just makes something very simple. There's no need to always try to do the most complicated machine learning model And I can also assure you that it's a good experience that your personal money on the line like It's a good experience in the sense of When you lose some money, then you're really going back and like monitor You will make sure that you're really doing good monitoring there and Yeah, another big point here is that you don't need machine learning to create training and test sets Or run simulations, right? So machine learning is just one part just running simulations where you know like the things that I'm doing is like You know just two values or something. I'm trying to find it's not not based on machine learning and a lot of just yeah You do tests backwards, but it's not it's not necessarily machine learning Yeah, don't underestimate the work necessary next to machine learning. I didn't bring that up But yeah, I'm it takes so long before Yeah, because you're depending on the exchanges to to trade and you know from idea to to actually have them to have something like that working it it takes a long time and Yeah, you can also do analysis sometimes instead of like forcing it to be machine learning and For the Python for Python right like simple can be better than complex It also holds for form machine learning or modeling or of any kind So another one that I made is X to Y I gave a talk about that also be Sometime earlier and it's the idea of automating this these these steps of like because a lot is you know You have some data you do some kind of pre-processing on it like missing dealing with missing values because otherwise it doesn't Psycho learn cannot deal with it You do model selection and I mean in the end after you've done a lot of like different projects You have a kind of you start to like a couple of models You know when to apply them if you just throw them together Well, you get you get if you throw this together, then you got something like X to Y and so so I'm loading that library of course and Reading in some data. I think it's this So that looks like this It's one of it's actually my favorite data set to be honest It's like who survived the Titanic they collected that and so you can say something about like this did Women indeed like was the captain last standing or these kind of you know these these ideas but Yeah, women did have a better chance. So that's that's good, right? Thinking that we don't have the most time anymore, but let's see how far we got So I'm going to get you the data again Survived so that's like one is survival zero is not so survived and We have to remove this like so now it's not there anymore And then we can say okay same pattern as before Except now we're like this is kind of messy data. There's missing values There's text and whatever and so I could learn cannot deal with that So the idea was you know, let's just do something. That's very simple There's also similar to the example code, but what what you can say is like let's fit on Half of the data. That's for the people that don't know like that's how you can get half It's a simplification so now it's training and Then you can use it to predict so there we go then you can compare if the Predictions are actually equal to So in this case we got 77% correct Yeah, so the idea here is that you know you have You have image data time series text data and you know There's so much that you have to do like pre-processing if you just start again It's nice to kind of bundle things and this is kind of the thing that I also would recommend to companies Make like this kind of a platform that does this kind of pre-processing for your common things, right? If you're concerned with turn Then make sure that you're like the main things that can be predictors of that are actually going to be there Take already care of pre-processing cross-validation and like what is going wrong with my data. You can do that all and Yeah deal with your core domain features and I mean only the final step is actually the models so You know like just bundle it and if you can make a quick iterations like that's that's going to help you like in a company So then you can see okay, we're missing data or let's add this data and it will be very quick. So it's important But then of course there's always productions I mean that's like the next step there so that that always takes more time like compliance like Proper development cycle. So make sure that you have that as well okay, so Gave a lot of Through a lot your way Let's let's wrap it up in the end machine learning is just a tool But it can be really powerful in the right circumstances like learning this kind of function between your input and Something that you want to predict But it's not more than that right so it's not Like that's some people don't really understand that they think out everything is going to be automatic with machine learning You have to do a lot of work around it Thinker ask yourself Is it easy to create a feed loop feedback loop here? Or if you have to do a lot of effort to create this like new data new annotated data where you get the answer Right like if you cannot collect income data, then it doesn't matter if you have age and it's a good predictor Which is yeah, so this is a very important one Yeah, don't forget to think yourself like what could be useful features, right? It's a bit of a simple one, but yeah Also, I think plugability ski don't try to solve everything in one model make different models and spread out the problem And I think actually that it's going to be very interesting to see what in the next few years People are coming up with models that you can then use in your model Because you know if you look at OpenCV and computer vision They can do facial detection and these kind of things, but it took a long time for people to yeah to build this and But once we have these kind of models for machine learning it will be nice to chain them together And don't try to solve the most complex problems if you if it's if it's like way too complicated Data or you know, like there's so many rules then you know just start with something easier like Especially when many strict rules are there like insurance companies banks, you know, they have so many strict rules if you cannot explain it if you cannot You know cannot reason why you're doing it or if it's obviously wrong why you're doing it like Discrimination or whatever then it's not going to work so and Most people find optimizing models fun, you know get the better score But you know optimizing the model is usually not the best like thing to do here If you have the simplest model, you can still really make big improvements by getting better data Or you know talking to the people that can help you get better data. So this is also a very important one and Never underestimate the work required besides machine learning to get it actually in production Right like even if you have the model, you're very happy with it You know, it's takes time to get it to work in size a whole application environment Build a framework your company Yeah, so I wanted to thank you and Comments say hi If something wasn't clear to you or you want to discuss your own examples We're just chitchat. I'll be here until Saturday and my final and most important suggestion is Make little projects and then give a presentation about your machine learning projects at the next year of Python Thank you Thanks very much. I have a few minutes for questions if anyone has it Have you actually made money on your blockchain project with question? It's you know, I have not lost anything yet. I'm still in the like development phase and Projections are that even if Bitcoin is going down 20% per month, then it should still be okay. Sure. Nice. Thank you Anybody else There are some cases where plugability could hurt performance for example in the Lightness prediction model you were showing Suppose there are like two places that are close by to each other, but The you would want very different brightness values for those and Since the prediction is based on classes like you just predict the place If it predicts the place incorrectly, it could really hurt the performance of the brightness Prediction. So what would you recommend doing in those cases? Well, yeah, it's a good question The the thing there is, you know, you're there's so many other features So you just hope that you know the model will learn to prioritize others So, I mean if you are afraid that it's going to be messy this Prediction then it's the model eventually will learn that it's like not an important feature, right? So then it wouldn't use it. It's you know, I guess in In the example of you know being at Euro Python or somewhere completely different then, you know It's going to be it's going to learn that that's in that case a good example But maybe, you know couch one couch two if you want to learn that difference very close to each other Yeah, in this case how it's parameterized I would expect that it's not going to put too much effort on like on this one So it would just instead focus on on bright like like time or you know the Yeah, the pixel value or something like that. Yeah, thank you Thanks anyone else for the question No, okay. Um, okay. Well the next talk is in here at 10 past 12. Can we say thank you again to our speaker?


Hey, this is Christian Baklu with another MVP Buzz Chat, and I'm glad to be talking with an Enterprise Mobility MVP today. I think you might be our first one, but Joy, hey, welcome. Hi, Christian. Thanks for welcoming to your chat show here. It's a pleasure from my side to be having a chat with you here. It's great to have you. Why don't you give people that don't know you?  Yes, sure. So my full name is Jamaliya Basura, but I generally go by the name Joy in short. I'm from India. I have around five years of experience in this IT service sector. I am ex MSFT, but I presently work for ATOS as a senior consultant architect for digital workplace solutions. So basically my day to day job is like engaging with clients helping them in their transformation to the modern workplace. And like I primarily specialize with Microsoft Intune as the endpoint management solution and with a little bit of engagement in the Azure AD identity and access management part. So that's all about me. Yeah, on the mobility side, again, it's, it's, it's funny. I do a show with other MVPs and we do kind of Q&A answering questions for the community. And I'd say every week there's one or two questions that are in and around Intune. Yeah, because the, I would say the product development team at Microsoft, they are so fast in bringing out new features. And even while working on new features, something sometimes breaks up the previous features that were previously working and things like that.  Intune being fully managed from cloud, you do not have any insight into the backend what it is doing. And in there like what you have is a portal where you just configure things and apply the policies. But what I generally feel is like, it's good to have a knowledge of the portal like how you configure the policies. But it's also equally important to know that how those policies are actually getting delivered to the endpoints and how it is actually working in order to like have a clear understanding of how the product is working. Otherwise, like this type of questions. And these are like general like to be honest, these questions are not invalid or something like that. These are genuine questions which comes up like sometimes like BitLocker is not working. I have deployed in point encryption protection policies from Intune but it is not working. But then at the end of the day, what have you done from the troubleshooting steps have you checked the BitLocker API events and things like that. So these are the things that many people are not aware of like where to look for and what to look for, which basically I try to help with my blogs and the engagements that I do so. That's an important point, because a lot of people I know when the, a lot of the shift from on-prem solutions to the cloud was happening, a lot of IT pros that were concerned about what's happening to my job. And is this, you know, is this all just this knowledge and all the training and all my experience, you know, is it all for nothing now it this these third parties these cloud vendors that own that activity. But to your point, you need to have people that understand how those services are actually running. It might evolve and change that role, but you still need to have that knowledge internally. Yeah, and definitely like when people. Yeah, I also see in my organizations where I work like people who used to work with SCCM and things like that or who are like highly experienced like eight years or 10 years of experience with SCCM like what is going to happen with it. Is it going away? Will Intune take its place and then I have to learn Intune. SCCM is not going away. SCCM is here to stay and it will be there. But at the same time, like if you are comfortable with SCCM you have been working with that, then Intune is also a same product from the Microsoft that is aimed to help you get a better modern workplace experience. So, like, I believe it's fair enough if you can invest some amount of time in learning it, rather than pushing it away like it's a new tool. Why do I need to learn it. Right. Well, I think it also helps for for organizations kind of go back to an earlier comment you made about, you know, adjusting to the to the cloud and how, you know, different it isn't and the volume of features, because we're experiencing that across every workload. You know, coming out of Microsoft, you know, especially in the modern workplace side of things, which is encompasses kind of all of Microsoft 365 and all of the, you know, side products. Yeah, but with all of that is to, I think people are, again, a little bit biased we work in technology and so we're a little more, you know, kind of in tune with, you know, not trying to use the product name but we're, we're, we're up to date on on the software development lifecycle and when we see new features that are released and we get excited about it. But just to do to almost kind of, you know, take a kind of a steady approach to that to be aware that hey there needs to be time for you know bugs to be figured out that there could be to your point depending on how a features being rolled out to be this example over and over again, you hear about a feature that's gone generally available GA, and yet it's not yet on your tenant, or there's something on your tenant but you're getting weird behavior that other people are not experiencing, because it might be acting in combination with other features other products that are on your tenant that are not on somebody else's tenant. So that whole idea like we're getting innovation rapidly, but needs to be tempered with this. I think the reality of, hey, but then it takes time for these things to, to be, you know, that that dog food experience. I know Microsoft is a both both of us former employees that phrase of dog fooding our own technology or own is great. There's only so many scenarios you're able to flush out and it's inevitable. Well that greatly reduces the number of bugs and issues that that the general populace experiences. That's why Microsoft does rings they do that internal dog. Then they do that fast ring for companies as they give us the raw, the, you know, the latest version and understanding that we're going to discover a whole new batch of bugs and issues and provide that feedback back to Microsoft. This is definitely true, like, because we are both ex MSFTs. We all know that MSIT or MSFT is the largest customer of Microsoft for its cloud products. So Microsoft has got a fantastic amount of volume or a pupil to test on before they actually test it and they actually plan the releases very well, like even if a new feature is rolling out, it will not roll out to all the tenants worldwide at the same time. It's in a phased manner and that is why we see that, okay, February week of 18. There is some new feature releases. So it's not there in my tenant as well because it's still under the roll out plan. So things like that it happens and that is why you have the insider preview tenants and all those things where you can actually go out and check out earlier than before it makes the availability in the normal tenants there. Yeah, and obviously, like, say, for example, it is not like, say today there is a policy that is not working, which is not. Well, I will say it's not a configuration issue. It's not an endpoint issue or a device specific issue, but it's a issue of Microsoft service does not means that the entire in tune service in hold worldwide will have that issue. So it can be a tenant specific issues and we have seen that where there are some bugs related to that particular tenant, which the backend team fixes out so things things like that this happens in the cloud side and yeah. Yeah, and it's just something that you need to, again, set your expectations your your it organization, it may change where some of the, you know, the ownership of the platform, you know, lives but to be clear on what are the SLAs that your organization does in place, understand enough about the service to have a better idea of what's happening. And so as you get that information back from Microsoft of what might be happening in your tenant that you can relate back to your end users, something better than. Definitely well with customer. Yeah, it never works well in the service industry you know like today if I am going to raise a ticket with Microsoft premium support then I would want to fast resolution but being on that side also I know that we have to go through the process we have to collect the logs we have to diagnose those because you come and tell me today that hi I'm facing this issue. I may not have a quick solution to give to you but maybe some some of the issues will have a solution some of the issues may not because those requests are deeper analysis and the diagnosis of what is happening because say for today if I am I speak to you as a Microsoft support now from the past experience so even like if if I have to troubleshoot a issue of yours in your environment. I need to have some prior knowledge of your environment. Because without that then I won't be able to help you up and and getting those details from the other side is sometimes a pain. Because also there are a lot of stakeholders that you need to involve in the calls because not everything is under your control or you would as an admin like even if I am I talk as an admin I may not have access to the conditional access portal because that is a feature of identity and access management but if the Microsoft support person asks me then I have to get someone from the identity team involved in the call we have to schedule another and this is how the delay goes on but obviously at the end of the day everyone is just trying to do their job and get it fixed but it's it's the patients that you need to show when a problem comes up because there is a great team out there which is there to help out and even like most of the times you can just when even like us like when we face issues before reaching out to support or anything else we would be first going out and checking out the community like if there is already something mentioned in there or if someone has already worked on some things so that I get some notes on there or things like that. So there is a great bunch of people out there who are ready to help if you know how to get the help. Well and that's well yeah there's again that's good training I think in general of you know for any employee to help them to understand what is the best way to make a request and if you're experiencing technical issues like what to go and be aware of what to document what to go and do. It's why you know as IT professionals we're always frustrated and we share frustration when we dial in to support and they walk us through like if you try turning it off and on and kind of questions and walk you through like you know is it on like what browser version of all the basic things with like look I've gone past all those things like yeah but unless I know I go through the steps it's all we've done is we've moved that conversation which used to happen with internal it over to you're working with Microsoft to resolve it but you still have to collect that information. You still definitely steps in that process one of the benefits while maybe it may feel like and likely it is like longer on that that activity to turn around time and work go through Microsoft. The benefit however of using a cloud service and working with Microsoft said like this is is on the back end when you start identifying issues Microsoft is able to go you're not just alone as you and IT department with your deployment on prem. They're actually able to go so yeah we're seeing dozens of companies that are experiencing this and here's what we've determined here's what's worked for these other organizations. So you're often able to get for those larger issues that are the software solution based you know based problems. You know more data and a faster response to those kinds of issues versus going and trying to do it on your own. So most of the most of the critical issues related to cloud because the enormous amount of data that Microsoft collects from his services. The telemetry like I don't believe any any other service actually collects this amount of telemetry that Microsoft collects and even before like a service will make a hit Microsoft will have a alert that something is wrong. And that is why there are like you get those service health checkups in the portals where you say that something is going for a periodic maintenance or something is going down then the team is working on there. But still yeah even after that there may be tenant specific issues but then those those say if I if I say a tenant specific issue it does not mean that it is specific to the tenant it is specific to the scale unit or the MSU. So whoever other customers are there on that same MSU or the ASU unit they will be facing the same issues as well. So sometimes you may be the first sometimes you may not be the first because there is a global support out there and you do not know if any other organization is also facing the same issues or not. And obviously there are solutions there are things that Microsoft comes up with and things even if it is not a solution at that moment at least they will come up with a work around. Yeah. Yeah. No exactly. It's well I mean like anything you know collaboration that's the benefit of collaboration. Yeah. So you've got to your wider net to cast out to try and and find your examples and solutions. Yeah. So what what kind of stuff are you actively presenting on so and for those again that are watching like he brand new MVP so congratulations again to that. Thank you. So so what kind of things are you actively talking about presenting on writing about out in the community. So I actively write about. So basically like MDM takes this is my blog where I write about the endpoint management with in tune things but most of my blogs do not talk about like how to configure things because those things you can easily get out from the Microsoft docs and things like that. But mostly if you if you have seen or if you have followed my blogs or if you have followed through my video sessions that I give the training sessions over the things. I mostly talk about how things are working inside like from the endpoint perspective so you as an IT group because if I'm working with in tune today and I'm not in Microsoft I do not have the Microsoft back and to go and analyze data. So whatever I have is the endpoint to work with. So how you can better use that endpoint to get an analysis of how the policy is working and whether it is working or not. This is something I put emphasis on and like if I say so currently I'm working working on a few topics which are currently in preview like the. The temporary access temporary access pass tap for the going password live solution with Azure AD then I'm also working on some interesting things with endpoint analytics the remediation scripts that you can do. And so things like that this is this is currently what I'm focusing on and like as I said I mainly focus on in tune and how you can better learn in tune from the endpoint perspective not from the service of the portal because you have to have to understand like. If you are today in a problem what you would look for and where you would look for instead of going and asking or things like that so for today example say for example I say you are having you are facing a bit locker issue and you come to me saying that hey I have deployed this policy and it is not working it came up with the error. So I would obviously ask for what is the event that you get on the bit locker API but if you don't come up with that and I tell you OK go and bring me that that is a delay. So when you are working with a policy you should be knowing about where and what to look for for that particular policy and these are the things that I like try to put emphasis on. Yeah now again that's great advice whether it's for end users or it pros that are managing these for their organizations to understand like the core information that a support person is going to want to have to help resolve that issue things that you should be looking for. Yeah it's it's important to to understand all those components. Yeah but that's a yeah again it's it's it's really important to understand how do I you know what do I need to provide to work with support with my you know engineering or it organization if I'm you have that relationship I'm managing that with Microsoft. What's going to be the most efficient that's going to get me you know so I'm not having to go back and go find any of this you know every time I want to report issue I'm going to go in go through kind of my steps have we answered everything so that it's the most efficient. You know use of both of our times and I contact Microsoft to resolve that. Yeah definitely so like being in the support in a service based industry or being in a support in a product based company. The formula for support is same like if you have an issue and you support or you raise a ticket or submit a request for help. Then you need to provide with the details that is there and if you provide the details at the same time when you submit a request it makes life a lot easier for the support person. Yeah that's right because that's yeah you're right you remember it's you know it's as frustrated as we are with having to go through those those basic questions per person. You think they enjoy it every conversation that they have starts that way you know. But anyway yeah well that's that's really interesting stuff so well it's great well it's been great to get to know you and learn more about what you do and and of course in the in the associated blog post will help you. If you have you know links and things that are out there for the folks that are watching the video or listening to the podcast. How can they find out more about you or get in touch with you. So. So basically my website is is my name only so it's you can just type in join earlier dot com and you can get to MDM tech space and you get my all contact details from there. You can find me in Facebook you can find me over LinkedIn definitely connect with me and you can also find me over Twitter but like I won't be able to pronounce my name here all over this because it will also. We'll provide the links and stuff it'll be out there that you'll be able to see it. Yeah so so at the end just type in join earlier dot com and go to my website the blog site and you will have all the links to get connected with me there. Excellent. Well joey it's great to to meet you and congrats again on the MVP award and and we'll hopefully see you maybe next year next calendar year at the next MVP summit I think the next time in person so. Yeah definitely because yeah it's still going to be a lockdown year again in 2021. It is it is unfortunately so 2021 is a lot like 2021 so all right well well thanks a lot we'll talk to you soon. Yeah sure bye.


So, first off, this is not a presentation for any kind of parents. There are some parents that are not going to be interested in this. For instance, if you want your child to be happy and you're fine with that, or if you're fine with your child becoming an artist or operating a BNB in Maine, this is not a presentation for you. It's for tiger mothers and tiger fathers for this presentation. So this is a child in question. She's nine. You can see her now involved in some uneducational, nonproductive activity. And that is not going to, I'm not going to allow this to continue. But thankfully, she loves Minecraft, and that's great. So this is Minecraft. This is how it starts.  That's your hand on the side there. And you find a tree and you chop it up. You make planks of woods and sticks. With that, you make pickaxes. You mine for rocks. You build houses. Sometimes you fight zombies, but mostly you build houses. And bigger and bigger houses. So it's not surprising that when I ask my daughter what she thinks she's learning from Minecraft, she says, hmm, wood is important. But of course, there's much more to learn from this sand. I forgot what it's called, but this game doesn't really have a goal. But there's real knowledge to be gained from Minecraft. And for instance, there's something called redstone in Minecraft that stands for electricity. You can actually build circuits. It's also obviously it fosters creativity. So for instance, if you want to decorate your house with a pit of severed heads, like my daughter did, you can. It's possible. Minecraft also fosters flexibility. So this is a study done in Sweden about how kids who play with Minecraft are very apt to scratch their plans when they discover new resources or new tricks in the world. So for instance, these kids wanted to build a village, but they changed their plans when they discovered that they could carry water in buckets, and instead they did water slides. But creativity and flexibility are low-hanging fruits educationally. These are the character traits that I want my daughter to have. These are the keep schools say this leads to success. So does Minecraft help me with these? So for instance, there's a problem of the tree house.  So what's the point? So I called Katie Salin and I asked her that. And she said, yeah, it does seem that building impossible architecture would be a waste of time. But what really happens is that when the kid then goes out in the streets, finds a tree, we'll look at the tree and starts asking questions. Like, well, could I put a house on that tree? Why not? What would I need to change to actually make it happen? And that puts the kid into a mindset of problem solving and that's really valuable. And okay, but there was another thing that I wanted to teach my kid through Minecraft and it's to be brave. And it says on the website, brave players. But my daughter, when she plays in Minecraft, she's very risk averse. She doesn't fight the zombies. So I asked Katie, because I had her on the phone, and she said, well, bravery really is grit and perseverance. And you can cultivate that by setting yourself challenges and achieving them and then sharing the results on a platform like DIY to get peer feedback or parents' feedback. And that's really important because that's your reward and the kid will be more amenable to taking risks if there's a reward. And that's my favorite part of Minecraft is that we talk a lot about what's going on inside her Minecraft world and we research ways to do things together on YouTube and we bond over it. So these are the things that Minecraft can teach and it's not really that much different from my original list and it's not so bad for a simple video game. And so now the only thing that I have to worry about is how to handle the pit of severed heads. Thank you.


Hello in this lecture we will define direct materials according to fundamental accounting principles while the 22nd edition the definition of direct materials is raw material that physically becomes part of the product and is clearly identified with specific products or batches of products. Support accounting instruction by clicking the link below giving you a free month membership to all of the content on our website broken out by category further broken out by course each course then organized in a logical reasonable fashion making it much more easy to find what you need then can be done on a YouTube page we also include added resources such as excel practice problems pdf files and more like quickbooks backup files when applicable so once again click the link below for a free month membership to our website and all the content on it when we think about direct materials we're often thinking about a manufacturing company a company that manufactures inventory processes inventory and we're thinking about how we can break out the costs of that inventory within the manufacturing process one way to do that one way to think about all inventory is materials and labor and overhead oftentimes when we consider inventory we only think about the raw materials and we don't think about the labor and the overhead which kind of makes sense if we're buying the materials the inventory from a third party and we don't see the labor and the overhead we generally think of something like a tablet like a bunch of raw materials that are put together however it's important to note that somewhere in the production process of course a huge piece of the cost the value of that inventory is the direct labor the overhead the things needed to convert the raw materials to the end product being the tablet in this case materials here would include things like the materials for plastic and the metals that would be involved those are things that would be physically part of the inventory as opposed to the labor that would be involved and be part of the value be part of the cost but of course wouldn't be physically part of the end product of the inventory and then we have the overhead another conversion cost again included in the price of the inventory however not actually physically part of the inventory


Wow, how to turn tables, team keep it clean.  So that would explain this random sickness that he just so happened to get that John Hardball talked about. And again, he did say Lamar, he wanted to practice. He tried to get to practice but he couldn't make it to practice. Maybe he was saying that because of the timing of the birth of the baby, maybe that was it. But if this is the case, congratulations again to Lamar Jackson, that man is really apparently, he really starting a family. Like he ain't playing around boy, but wow. That's definitely a change of events. You know, it's funny because if this is the case, it's funny how things can change like that. So many people, they just continue to speak ill, no pun intended there, but to speak ill of his immune system saying, oh, this and that. I saw somebody even say, oh, well, this another reason why Lamar Jackson does deserve the money because he's always sick. And I just, it's crazy with how, like with a football player, professional football player, obviously these guys, a lot of their lives are on public display, 24-7. And it is hard for them to have any sort of privacy because it's always something going on and everything that happens with them, a lot of it gets publicly documented and whatnot. They pay the hours that they work, everything is on public display.  But anyway, whenever in the past, whenever they've said he's sick, it's usually once a year, sometimes twice, but usually once a year around the same time every year. And there are a lot of people that get frustrated with that. There are a lot of people that get really upset with that. And I'm thinking like, man, I guess these people, they just never get sick. They never get sick, they never get colds, they never get anything.  And a lot of people were catching that virus, but when Lamar caught that virus, that's when everybody was like, oh man, he's, or not everybody, but a lot of people were like, oh man, this guy, he's always sick and he's irresponsible, this and that and the third. And it's just weird. I feel like a lot of people, when it comes to just a lot of stuff, not even just with Lamar Jackson, but when people put themselves in other people's shoes, then I feel like people's thought process would be so much better. And I feel like a lot would just run a lot smoother. If we put ourselves in other people's shoes, instead of just looking at somebody like, oh man, they should have done this or they shouldn't have done that or they need to do this or they need, put yourself in their shoes. Try to put yourself in this situation. I know a lot of times it can be hard because you can't always relate to everybody, but I feel like if people at least tried to, then things would be just so much better. But anyway, shout out to Lamar. If this is the case that he did have another child, congrats. So just like Lamar is when it came to practice today, but apparently it's for a very good reason. We out.


No! Fully raw, Christina! 21 hours ago. Jesus Christ, the vegans, they're stepping up the game. Let's watch Fully Raw, Christina. Let's do this. Stop it! Jesus. What up, my beautiful friends? It's Christina and I'm so happy to be back with you today for a new What I Ate Today video. It's been a while since I've made a What I Ate Today video and I'm excited to share with you not only some delicious raw vegan recipes for you to try and some ideas, but also some recent updates and changes in my routine recently that have completely improved how I feel on a day-to-day basis. Yeah, vegans always have to change everything up and make improvements in their fields.  It's just the little things, you know? It's just the little things. She looks absolutely anorexic. This video was sponsored by FourSigmatic so I want to send a special thank you to them. Every vegan is sponsored by FourSigmatic. For all of my mushroom lovers out there, I've got some special treats for you. I'm a mushroom lover, but I do not buy FourSigmatic. For you in this video. So let's get this day started. I'm ready to start making some food and get into my day. Are you ready to rock? Don't call it food. Rock and roll. Let's go. Some things that change recently for me and I'm feeling better than I ever have. Physically, mentally, emotionally and spiritually. The first thing that I've been doing emotionally and spiritually consistently every single day as of recent is hot yoga at 8.30 in the morning. Every single day. I have been very consistent with this and I just love my yoga practice. I love the sweating, the breathing, the moving and I've been combining my hot yoga with hip training three to four times. Nothing wrong with yoga. It's a week. My body has started to get toned and lean. Before this, I was a long distance runner and after a while I stopped seeing results. Another thing that I have been doing as a... Every vegan stops seeing results and now you don't see any results but now you're just shedding off body fat. Again, you don't have any musculature improvement. Recent is intermittent fasting and I really love it. My hours of eating have been... Vegans love intermittent fasting because they're eating less of those counter nutrient-laden foods and less of the fiber that blows them that much. This is why they love it. From between 11 a.m. to 7 p.m. I'm not eating past 7 p.m. If anything, I'll just have some tea. I'm still eating the same amount of food and my diet has not changed. I've just moved around my eating times a little bit. I've also really been focusing on getting better deeper sleep. This has been challenging for me with all of my traveling but... How do you focus on getting better deeper sleep? Considering I basically went 11 years on 3 to 5 hours of sleep each night I'm currently winning on... 11 years, 3 to 5 hours of sleep. And she doesn't understand that that could possibly have to do with the diet. You're running on adrenaline, on sugar. That's where you cannot sleep. 7 to 8 hours right now and meanwhile just... something I have to add to this. So you haven't been sleeping longer than 3 to what? 4 or 5 hours for the last 11 years. So as a raw vegan and you don't feel that this is something that you should share with your viewers, right? You are pretending to be healthy, vibrant, right? The epitome of health, raw veganism. And you do not tell your viewers that you cannot sleep. How is that healthy? If you cannot sleep at least 6 hours you are starving. That's where you wake up. Jesus. It makes a huge difference in how I feel. I believe I had massive adrenal fatigue at one point and I'm working to rebuild and restore. Even though my physique has changed lately I want to make a point that my diet hasn't changed at all. I'm still fully raw vegan 14 years no deprivation. I'm still doing green juice. Let's not see more. I'm raw vegan 14 years, no deprivation. But you didn't go into how she fixed her sleep. What did you do? You don't say what you did and then you insist that you didn't change your diet. Sorry Christina, I don't buy it. We know many fully raw and regular vegans that are not vegan that pretended to be vegan.   Oh yeah, basically everything on your app. Sure. So download that app and get right into it. Get healthy. Like Christina. Arriving more than I believe I ever have and it just shows that tiny changes can make a huge difference. What is the change? You don't have to give up what you love to see results. I hope me sharing these tiny things with you can be helpful. Super cringy.  They're downward facing dogs. Hold for you in some way because they have made a profound impact on how I don't want to see you sweaty arms. Disgusting. If you've been following me for a while then you know that I typically start my days off with green juice. It's my favorite way to get my. Yeah, that's what you do when you drink oxalate juice. You start dancing, of course. They're going so many minerals and this delicious savory juice I love it. So I'm making 32 ounces of green juice right now and I'm starting off by adding super toxic.  Ginger, celery stalks, oxalate into my juicer approximately two peeled limes. Ginger. One large thumb of turmeric. Turmeric. One large thumb of ginger. Yes. One cucumber. Three to four leaves of romaine lettuce. Four to five leaves of kale chopped. One large head of parsley. But honestly, has anybody ever asked themselves why would you juice kale? Honestly, no. No hate, really. Why would you juice kale? That doesn't make sense, right? There's nothing in it that you would need in a juiced form. Not at all. If you want to juice cucumbers, for example, okay, you could use that as hydration. I get it. No worries. I drink cucumber juice sometimes. Nothing wrong with it. However, what you're doing there, what is the benefit? And why do you tell people that you will get nutrition out of this? It's a lie. Or cilantro. And one head of celery. I'll run my green juice through a strainer so that it's super smooth and I will pour it into my jar. And from this point... My jar. Yeah, aside from that, this is at least $20 of green juice.  Non, you can take your green juice anywhere. You can drink it in front of your laptop while you're answering emails. You can take it to a workout class, whatever. I tend to drink my green juice right then and there. You can sip it throughout the day and even drink some before dinner. It's always nice just to have a delicious green juice in your diet on a daily. I recently did a... But why? Why? Just tell me why. Tell me why? One green juice a day challenge on my fully raw recipe app. So for those of you who are looking for some green juice recipes, I have tons of them. And I even... Have this challenge on my app that you can download in the description below. What is this? It's pretty... Fake smile. Fake... Disgusting woman. Clearly, I'm still doing this and having a great time with the results. So I highly recommend... Shaking your hips. It's repulsive. Recommend one green juice a day. For my second meal today... Don't kiss me. A lunch. I'm going to be sharing an ice cream smoothie bowl. It's kind of like a smoothie bowl. Yeah, more sugar. What is that? Nothing. Just more sugar. Without renaming it, I can already see it. It's cacao nibs. So great. Neurotoxin. What is this? Goji berries, some sort of berries, blueberries, strawberries, just a berry smoothie. Just sugar. But it tastes like ice cream and it's good for your body, the animals and the planet.  Why is it good for my body if it's just sugar? Why is it good for the planet? Why is it? Why do you simply repeat those old vegan slurs? Why is this good for the planet?  You want to get rid of them. 1,000%.  And it is delectable. Now I'm going to be doing something a little bit different in today's smoothie bowl. Typically I only use like two or three ingredients. However, more stigmatic has some pretty cool... Yeah, however, today I'm going to give you the full package of advertisement. Today I'm going to give you a four-stigmatic adaptogen blend mix. Full new superfoods and proteins just introduced. And I'm really excited to give them a try. Absolutely. For those of you who don't know four-stigmatic, they are a mushroom and superfood company who create all-organic, vegan, gluten-free... Yeah, those guys are geniuses because they catering to those deficient vegans that will count down anything that will make them feel something. Instant products that you can add to any smoothie, drink or tea. And after having researched the benefits of consuming mushrooms like reishi, chaga, cordyceps, and lion's mane, I'm convinced is it raw though? Taking these into your diet... 100% those mushrooms are not raw. No chance. No chance in hell. Not that I have any issues with that, however, just saying. It's not fully raw.  A minimum of two to three times a week is a great idea. So four-stigmatic has just come out with some really cool new stuff. One of them being their superfood protein that I'm excited to try. It also comes with adaptogens that apparently rebuild and repair muscle easily and help to restore overall wellness. Most proteins contain mushrooms, fillers, artificial sweeteners, etc. And this one does not contain any of it. It's organic, it's vegan, and it's also not flavored. So I'm interested to see how... So this one doesn't contain any isolates, you want to tell me? Okay guys, so it's really, really hard to stream when I go above 240p, which is absolutely laughable. However, I'm just going to put this onto 720 real quick. That's much better. And I will check the ingredients list. Okay, so what do we got? We got organic pea protein powder from the seed. Okay, we got organic hemp protein powder from the seed. We got chia seeds. We got pumpkin seeds. Okay, coconut, powder, fruit, whatever. Ashwagandha, stimulants. What else? I don't even know, I can't pronounce this, eluatrento. We have cordyceps mushrooms. Yeah, all the lion's mane, so on and so forth. Okay, so we have mushrooms as some sort of stimulant if you will, and paired with a lot of seed proteins.  Okay, so should I give an explanation because nature did not intend for you to eat her seeds. That's not what nature wants. Nature wants you to eat your specific diet, which would be obviously meats.  That's not what nature wants. We can still understand so therefore they're trying to strip away all the anti-nutrients as good as they can and then isolate those proteins and give you their sludge and sell it for horrendous prices. That's what they do. All this goes. This mushroom protein powder includes cordyceps, lion's mane, chaga, turkey tail, reishi, and mushroom blend mix. For those of you who feel like you need an extra pep in your step, this movie should do the trick. So let's get started on this movie. For the ingredients, I'm going to be using approximately four to five ripe peeled and frozen bananas. One large cup of five bananas, approximately 20 grams of sugar per banana. A hundred. Congratulations. Good idea.  Talk about a superfood protein packed lunch. This is definitely it. No, that is not superfood lunch. Superfood lunch would be a fat, juicy steak with maybe some chicken liver or some beef liver, some salmon roll, some sashimi. That would be amazing. However, what you are choosing here is just a bowl of sugar with mushroom extracts. It's not a superfood. You're still lacking crucial nutrients and vitamins in that thing. That's by no means complete. And this until it becomes completely smooth. The more coconut water that Yeah, completely smooth. So you get less digestive issues.  Nobody does. You add here, the more the smoothie it will be and the less coconut water that you add here, the more ice creamy it will be. It'll be thicker. Pour this into any bowl of your choice. And you can add on toppings. You are anemic. And this is why you're craving ice cream. Like sweet cacao nibs, some shredded coconut, extra berries, whatever makes you happy. Ladies and gentlemen, this is my nice sugar content makes you happy. Smoothie bowl for lunch. If you're interested in getting any of Orsignatic's new products today, you can get up to 35% off of everything that I just mentioned. I don't want any off. I don't want to buy your stuff. Christina, thank you very much by using my specific link in the description below.  This will last long. So if you're interested in any of these products, please go check them out now and give them a try. I'm not interested. Yeah, great. Yes, yes, yes, we have so much fun delicious food. My third and final meal for dinner. I'm going to be making wraps with an Asian dipping sauce. Jesus. I wanted to share with you something. Okay, come on, guys. Does this look like human food? Really? Does this look like human food? Or does this look like something that you would find in a flower shop? Right? This is something that I would buy my mom for Mother's Day. Okay, this is something that I would give my girlfriend as a birthday present. Maybe I would bring this to a date as a beautiful flower bouquet. That is not food, Christina. I think a little bit different than a salad, since I typically do salads or zoodles at night. And this is a perfect colorful alternative. And they're fun to share at any occasion. For this recipe, you're going to need some large colored leaves and we'll prep them simply by trimming off the back of the stem and cutting off the bottom of the stem depending on how many people that you're preparing. Is anybody salivating seeing this leaf? Does anybody here want to eat this? Does this look like food? Pairing for, I would say approximately four to five colored wraps is a good amount to eat or at least that's how many I can get through. If you have a big family, then definitely prepare for more. Once you have your leaf ready, go ahead and turn it face side down so that you see all the veins on the back and begin to layer on all of the ingredients of your choice. I'm going to be using some purple cabbage, some shredded carrots, some thinly sliced cucumbers, tomatoes, rainbow bell peppers, yellow, red, orange and green. I'm even going to add in some shredded beets here to give it some. All of this is condiments at best. This is something that you would might have on the side. If at all, none of those things is nourishing, none of those things. In color, some mango to give it a little sweetness. I love mango in these rolls. Yeah, of course you love mango because mango is the only thing in there that is actually somewhat digestible. That's the only thing that gives you sugar again, straight away and therefore makes you happy. And if you want a little extra something, something you can add in some sprouts. Last but not least, we're going to add in some. She's so cringy without knowing it, man. Sliced avocado on top. Yeah, to maybe make some animal fats.  It's a collard wrap burrito basically. You can always use a toothpick or a string to tie these together to keep them wrapped up a little bit more firmly.  Nobody wants to eat that, even if you enjoy a salad here and there. Okay, no worries. Nobody would like to eat this thick leaf. You're not a herbivore. You can spread some guacamole inside so that they stick together better. For the sake of keeping this recipe simple, I'm just using fresh veggies here and we're going to make a dip. This is exactly what our collard wraps will look like and they are gorgeous. Yeah, they're gorgeous to look at. They're like flowers. They're not edible.    No chance.  No chance she's going to eat it like this. There's going to be a ton of some sort of raw vegan sauce. 100% guaranteed. Imagine the fats after this plate. Now we're going to be making our agent dipping sauce and it is so easy and fun to make this sauce. The exact ingredients are in my recipe app. You can click in the description on the link below and it'll take you to my app. You can give it a download. I'll be adding into a high speed blender approximately two large tablespoons of sesame tahini. So now I'm going to show you tahini again and with a soy sauce or whatever that was. Sesame sauce, you name it. Doesn't even matter.   Ridiculous. Ew. The juice of two limes or lemons. A teaspoon. About a half a tablespoon of almond butter. About a half... Almond butter. Even more fat. Of course just vegetable oils.  A tablespoon of almond butter and if you want to give it a little kick you can add in a small slice of raw ginger into this recipe as well. Yeah because I need more poison. Blend it up until it is completely smooth and creamy. If you want it to be less thick add a little bit of water or even a little bit more lemon or lime juice. It's disgusting. Pour this into your dipping bowl. Show me how you eat the whole plate and show me your belly afterwards. And yeah if I would be into it show me how you feel on the toilet. Pour this into your dipping bowl of choice and voila you have a fully raw Asian dipping sauce. How delicious does this look? Now you can... It doesn't look delicious. It looks like flowers. Take your rainbow colored wrap and you can dip each one of these into your Asian dipping sauce. Ladies and gentlemen dinner is complete. Yum. I've been finished. Okay that is perfect. Notice something. Is it just me? Do you realize that your food just looks like the background? Just like the vegetation that nobody would ever try to eat? I don't see you bending forward on your force and trying to nip off those leaves. You wouldn't because you know that's not your food. However this here somehow should convince us to be nutritious.   Finishing my dinners around 7 pm as of recent. So around I would say 7.30 or so. And no more stimulants to kick it off. One cup of... Because now after this meal you feel terrific.  Absolutely fantastic. You feel horrible. That's the truth. This is why you have to use those stimulants. Mushroom tea. I usually do a mix of chaga and reishi. Something to calm me down and relax me after the day is done. I love these four sigmatic instant packs. It's so easy to make. You simply just have some boiling water and then you add in one pack of chaga or reishi here. You can add in any type of sweetener here that you like. I prefer coconut nectar and you have a delicious warm evening mushroom tea. Why do you do this? This cac face. Yeah one of them is enough believe me. Jesus Christ. Thank you so much for joining me in today's video. If you'd like to be sure to give it a thumbs up and comment below. I'm gonna make sure to give it a thumbs down. Jesus Christ. What did I just watch? Super cringe fest man. Cac face after cac face. Shaking my hips. Look at me. Horrible. Guys I think there was enough vegan youtube for a day. I can't take it any longer. Really. There was too much.  Jesus Christ. Remove. Stop it Christina. You horrible human being.


In this week's Fishing Tip, Ray and Manny discuss a great way to cover a lot of ground when fishing for all types of fish with bottom bouncers. The basic idea is you tie your fishing line to the bottom bouncer and then you have a leader or three or four or five feet long, however long you want it, and you tie that to the end of the bottom bouncer and then you're ready to go. You're dropping over the side and I'll show you the technique that we use here in just a second. But this is one style of bottom bouncer and it's got an attractant color on it. This happens to be a three ounce or a two ounce bottom bouncer and another style that I personally like because it's very simple to use and you don't have to tie anything.  Obviously I don't have anything hooked up on for bait here but I do have a little extra weight and then here we would put a crank bait or it could be a crawler, a leech or whatever and then that ensures that we're always going to be bouncing off the bottom one to two to three feet depending on how long a line you're letting back there. When using bottom bouncers there's two basic applications for them. One is actually simply jigging with them. So when you get, you release it over the side and that weight hits the bottom. You can simply jig up and down and then you know that that bait is within a couple inches of the bottom as you go. The other application obviously is trolling with them. So once you get them out, you get them down, you can feel when you actually hit the bottom when you're trolling with them. I like to raise them up a few inches and keep on trolling. For Lakeland News I'm Ray Gildahl with the Niswagai's League. And I'm Mandy Erick, the Bassin Biologist. And as summer comes to a close, that's our final fishing tip of the year. We'd like to give a big thanks to Ray and Mandy for all their hard work. Educate the people on some great fishing tips once again. Yeah, very interesting all summer long. Thanks to those two for volunteering to do that for us. Yep, definitely.