I'm gonna speak about your identity and data privacy in the internet. We created the GDPR compliance as a service for small and newly established businesses. It's something what every business right now struggle because of small and new generation of entrepreneurs just simply I don't understand the legal language and cost to meet requirements so you need to spend on the legal buyers to create the data privacy and privacy policies so you need to spend on your web designers so and of course the customer support agents or data protection officers to handle and exercise the rights of their users the GDPR about the strength and the IT systems and give their rights to the end users so we created the identity management platform it consists of three steps so first one is to generate legal documents we generate in the privacy policy and cookie policy especially for your business requirements especially for countries where you operate the secondly is content management forms and data collection forms we notify the users on how they have to keep away the data of course and how the business is using it and those cookie content management forms and data processing we match the users data when they want to exercise the right of the users with your databases with your CRM account management platforms the MailChimp and etc so it's omni channel communication between all of them it goes the GDPR goes with identity all the time and data processing we target small and newly established entrepreneurs it's more than 300,000 appears each month in Europe and it's only five for 500 euros per month be compliant and be loyal to your users we are legal and cybersecurity professionals from Estonia working with e-government and identity verification providers and banks we also been accelerated in Switzerland being one of the proof of concept for cybersecurity insurer and we are underwriter for them we have the advisors such as cybersecurity strategy from Microsoft the legal professionals and cybersecurity from the payment industry as well trust us we legally audited by the void bar card is also one of our compliance agent the CHOP is provides us the cybersecurity and PWUC the knowledge base for us we already profitable 25,000 MRR and we helping to 900,000 people to exercise the rights personal data is a personal value thank you I have a question and it might be a little bit naive but I do those companies need to pay a recurring fee to keep compliance or is this something that they check once in a while with their lawyer like once a rate six months and and that should be enough yeah thank you so basically we are lawyers are really expensive it's the first one and the secondly we are actually in a way in this space because if you want to create the privacy policy you are paying once and you pay 2,000 euros for one document but interpreters please pay 799 and we will update and we constantly update your privacy policies you based on your regulatory changes in your countries of operation and that's actually the way by paying the spot like you are paying 799 for your Spotify please pay for privacy policy the same price and it's gonna be like constantly updated why not too and what what about startups I understand but what about bigger companies when they have more a dog solutions or are you going to stay with various mall companies that they do it themselves we do have two types of customers so one is newly established businesses and since we are connected to info registers we know when the business is ready to create the website and we are just coming and saying look if you are creating the website you need to make this GDPR compliant and the secondly it's e-commerce's they do have multiple CRM's databases accounting software etc and if we will implement the data collection tools on their website this data will streamline go goes to all databases they have and it could gonna be updated also recently so customer support agents will minimize the time on finding those identities in fragmented databases and it's going to be only in one click in basis ID yeah thank you very much


Are you proud of Jesus? Are you proud of your relationship in Christ? Are you proud of what you've done in Christ? Or are you proud of what Christ has done in you? Jesus makes a statement, if you are ashamed of me, I shall be ashamed of you before my father. But if you confess me before my father's in heaven, I will also confess you before him. Many people today kind of hide and are ashamed of the fact that they are Christian. They don't wear it as a badge of honor anymore because other people have, in their eyes, have impugned the name of Christ. Well, those people may or may not have been Christians, but it doesn't matter. I'm proud of him.  Let the redeemed of the Lord say so.


Good day, fellow investors. Now commodities should be an essential part of every portfolio going into 2018. The International Monetary Fund has increased global growth GDP projections for 2018, which means we could see higher demand for commodities and inflation, which is again something good for commodities and the commodities part of a portfolio should do very well. Let's see the global commodities environment, what's going on, what can happen, what are the risks and reward and in what commodity you should invest or be overweight with your commodities part of the portfolio. As said, these are the projections for growth, global growth, average around 3.7%, emerging market and development economies above 5% growth, advanced economies around 2% growth. Very, very good. The higher growth in emerging markets will come also from commodity exporters and the projections for the next five years are that commodity exporters will have a bigger chunk of global GDP growth. This means that investing in such countries, emerging markets and commodity producers should be good according to the IMF in the next five years. So, rosy projections, always be careful but let's see at the different sectors and different commodities what can happen. If we look at what Glanker says about the commodity sector, copper there has been no wall of supply, there is an expected deficit, cobalt is enjoying electric vehicle demand, zinc has supply cost rates, lead is underpinned by again supply challenges, nickel is crucial to electric vehicles and still lowly priced, thermal coal, powering Asian growth and urbanization. So, if we look at of course from a positive perspective that Glanker has, everything looks good for commodities. And if global growth continues for the next five years, unstopped without shocks like it has been the case for the last few years, then we could really really see great returns on investment from commodities. Glanker is of course a diversified play. However, just two years ago, the end of 2015, Glanker was almost going bankrupt because when the environment for commodities changes, all hell breaks loose. And that's the risk you have to always keep in mind when investing in commodities. Tight margins, when things are good, margins increase exponentially, when things are bad, margins become negative very quickly. And therefore, you have to allocate only so much of a portfolio that can weather that volatility. And that's something very important to keep in mind over the long term. Let's see what happened to copper 30% increase in 2017, which is very good. I think copper can go much higher if there is higher demand. We can see above far above 5%, especially if economic growth continues and this deficit in copper widens as it is expected in the next few years. There is simply not that much copper anymore. Zinc prices are also at multi-year highs, which make investing in the sector riskier than it was in the past. Nevertheless, demand is strong and there are really supply issues. Iron ore prices have had a terrible time in the last five years, but have been showing strength in the last two years. And this shows what can happen to commodities, also on the upside, as we have seen in 2012-13 with extremely high iron prices, but also on the downside. And that's terrible for the stock. A metal that still shows subdued prices is nickel. The low prices are due to extremely high inventory levels around the world. However, those levels are declining and demand is increasing. And there is more demand than the amount produced. We can expect a similar situation to happen with nickel as it has been the case with copper and zinc. Therefore, also, nickel is my favorite metal to be invested in, going into the next few years. The positive outlook for nickel comes from expected increased demand for batteries that will also increase demand for copper and cobalt, of course, lithium and other metals. We can see here how much Glencore estimates to see higher demand from the electrical trend. It's something I really want to be exposed with my portfolio. There is always the risk, but you have to know how to manage that risk. So commodities look good for 2018, not as good as they have looked in 2016 and 2017 because the price is up 50% for zinc, 30% for copper. The higher the price, the higher the risk. That's a given. Nevertheless, there is still much upside. If you have your winners, let them run because there is still strong demand. Everything looks good.  Of course, I've discussed metals, I've discussed food fertilizers and whatever fits the environment and an all weather portfolio in the future. Thank you for watching, looking forward to your comments and I'll see you in the next video.


Coffee is the most popular beverage in the world, with more than 400 billion cups consumed yearly. As a matter of fact, almost 65% of Americans drink a cup of coffee every single day. However, this, once believed to be a healthy drink, has started losing its popularity due to the severe side effects that it causes, such as anxiety, stress, nervousness and jittery. The biggest problem happens when you drink a cup of coffee in the afternoon, since it can stay in your body for up to 10 hours, which can ruin your sleep. But is there any alternative available? Maybe one that is not addictive and it doesn't cause any side effects? Well, finally, there is. Hi friends, welcome back to the channel. My name is Greg Gostingar and I'm the founder of Your Inception. If biohacking, nitropics, optimizing brain performance interest to you, then subscribe below and join our amazing community. Let me present to you Beyond Caffeine, a caffeine-free energy booster that boosts your mental performance, it doesn't cause stress or anxiety and you can actually drink it in the afternoon. Now, I've been drinking Beyond Caffeine for the past month and in this video, we're going to talk about its benefits, my experience, its taste and finally, I'm going to reveal whether this is an actual coffee alternative. So what exactly is Beyond Caffeine?  It was designed as an afternoon booster, so basically, you can still drink your morning cup of coffee if you want, but then in the afternoon, when you really shouldn't drink coffee anymore, you drink a cup of Beyond Caffeine instead. To prepare Beyond Caffeine, you just open the packet, put it into your glass and mix it with some warm water or your chosen milk. We'll talk about its taste soon, but let's first check my experience and the benefits of Beyond Caffeine. By the way, guys, how does coffee work on you? Do you suffer from any side effects? Let me know in the comments section below. Okay, so I'm about to try Beyond Caffeine for the first time. I'm going to try the peanut brittle, which sounds pretty delicious actually. So yeah, I've just prepared the drink already here. It's still a bit hot, but yeah, let me try it out and see how it tastes. The smell itself is, yeah, it's pretty good, a little bit artificial, but not too bad. All right, okay, this is much better actually than I expected. This one is, yeah, it's gluten-free, dairy-free, no added sugar, vegan and low in calories. Yeah, honestly, I mean, this is much better than I ever thought possible actually, because mushrooms and adaption herbs usually don't taste that well, but this is actually quite good. This is a bit sweet though, too sweet for my taste. This is what I noticed the right way. I prepared this in water. I guess if you prepare it in like plant-based milk, yeah, I guess it's going to have the same taste. Maybe the structure will be a bit better, because right now it's kind of a, looks a bit, yeah, not that thick, I would say, not as creamy as coffee. But otherwise, yeah, cool. So I'm going to drink it now, and I'm going to keep on drinking this for a while and then let's see if I like this drink or not. Now I've been drinking beyond caffeine daily for more than a month now, and I have to tell you that I instantly fell in love with this product. Here is why. Firstly, it doesn't cause any adverse side effects like coffee does. Now, even if you think coffee has no negative side effects on you, caffeine consumption in the afternoon negatively impacts your sleep, which can lead to a myriad of health issues. Now, I've been tracking my sleep with the Aura Sleep Tracker, by the way, you can learn more about Aura up here, and every single time I drank a cup of coffee after 1pm, my sleep quality was worse even if I didn't feel that right away. However, with Beyond Caffeine, this is not a problem anymore. The second thing I love about Beyond Caffeine is its formulation. It contains some of the most potent and well researched compounds that actually improve your mental performance, increase your energy levels, reduce stress, and can improve your overall well-being and health. So without any doubt, this is a safer and much better alternative to coffee. And the last thing I really like about Beyond Caffeine is its taste. Now, funny enough, that's also one thing that I don't like about Beyond Caffeine. Let me explain. So when I first tried Beyond Caffeine, I was literally impressed because I didn't expect such a good taste of this drink. Sadly, blended mushrooms and adaptions can have quite a bitter taste, but this one tastes quite sweet and it smells good. It even comes in three different tastes at the moment, hot chocolate, salted caramel, and my favorite peanut brittle. Even though Beyond Caffeine tastes much better than I expected, it is, in my opinion, way too sweet for me. Now, I personally avoid all the sugar most of the time and I don't consume any sweeteners either, so maybe I'm not the right person to talk to you about the sweetness, but still, I think that many people will find this taste a bit too sweet and artificial. It's not terrible, but this can definitely be improved. By the way guys, if you liked this video, please press the like button below. Now, if this is such a great coffee alternative, why would anyone drink coffee, which is addictive, ever again? Well the idea of Beyond Caffeine is not to take your morning cup of coffee away, but to present an alternative to your afternoon cup of coffee. And I think that's the right way to go, because the effects of Beyond Caffeine are not as strong as those of coffee. Personally, I've drank Beyond Caffeine in the morning many times and I loved it, but it doesn't give an equally strong kick as a cup of coffee. So my experience was the following. When I drank it in the morning, I had a boost that lasted for about two to three hours, but it was less effective than coffee. So for me, that was great, because coffee makes me nervous, unlike Beyond Caffeine. On the other hand, when I drank it in the afternoon, I got exactly the same effects, but I liked it even more. Because in the morning, after we expose ourselves to bright light and we properly wake up, we have lots of energy. In the afternoon, we naturally get more tired, so such a natural booster works even better than. Now, the formula of Beyond Caffeine is actually really good. It's a potent and tropic, but it is not perfect. There are ways to optimize it, like for example, reduce the amount of Bacopa Moneri, since such a high amount of Bacopa can reduce your motivation, but I will leave this to the brand. Now it dissolves pretty well, especially in hot water and plant-based milk, so it's really easy to prepare it. By the way guys, are you searching for the best natropics for your individual needs? If yes, go for a free brain assessment, link below, and get a personalized recommendation for the best natropics. Since Beyond Caffeine is healthier than coffee, it boosts mental performance, it provides multiple benefits that coffee cannot and it doesn't come with any side effects. It must be way more expensive, right? Well, no, not really. A package of 25 dosages for 25 days costs about 80 Australian dollars. Yes, this is an Australian company, but they ship to the US and to most other countries. So 80 Australian dollars equals to about 55 American dollars. So a daily dosage costs you just over 2 dollars, which is I think way cheaper than coffee in your favorite Starbucks. Now all of that sounds really good, but there must be a cat somewhere, right? Well, let's look at the pros and cons. The main pros of Beyond Caffeine are, it's a caffeine-free energizer, it improves your mental performance, unlike coffee, it doesn't cause any side effects, you can drink it in the afternoon, it tastes pretty good, it's relatively affordable, and it can improve your overall health and well-being. How about the cons? Well, the taste can be improved, as I said, this current taste is too sweet. The formula could be further optimized, especially for people who would want to drink it in the morning, like myself. It does contain lots of nitropics and vitamins, which you may not need. And of course, it's not super cheap. And that's about it. So is Beyond Caffeine a proper coffee alternative? Well, it boosts your energy, it boosts mental performance, it doesn't cause jittery, it doesn't ruin your sleep, it is healthy and it's definitely drinkable. So if you care about your sleep, if you don't like coffee, if you search for a caffeine-free brain booster, or if you're sensitive to coffee, you should definitely give Beyond Caffeine a try. Now there's a link below if you want to order it right away. And if you're searching for a potent brain booster in capsule form, check my review of Kualia Mind, my favorite nitropic snack. Thank you guys for watching this and I hope to see you soon again. Stay well.


TEFL jobs in the Middle East If you have a degree and a recognized TESOL certificate such as that offered by ITTT, you won't find a region in which you can make more money teaching EFL than in the Middle East. These oil-rich nations might suffer from a bad reputation and admittedly, they're not for everyone, but saving thousands of dollars every month will certainly make up for any hardships along the way. Don't believe everything you hear about the Middle East. Countries like the UAE, Kuwait and Qatar are much more liberal than you might imagine. And while the Kingdom of Saudi Arabia is still rather strict, it offers top dollar, paid accommodation, tax-free income and paid airfare. Salaries in the Middle East As mentioned, you won't find higher salaries than here. You'll need a degree and a TESOL certificate, but with those two things in hand, expect job offers to roll in just before you start rolling in cash. The two most important words are tax-free. If you're a U.S. citizen, you needed claim tax on income lower than 80,000 United States dollars per year, so this is not too good to be true. On top of tax-free income, you'll receive furnished accommodation, oftentimes transportation allowances, and in almost every case, free airfare to end from your location. If you've got bills to pay, but you still need to gain experience teaching, the Middle East is the place to achieve both goals. Jobs in the Middle East Most jobs will be in universities. Males will teach males and females will teach females. There is a growing market for language centers and teaching jobs within private corporations. Jobs are available year-round and finding work shouldn't be an issue with your ITTT TESOL certificate in hand.


We have a good network of hydrants that cover every single address in the city and we try to get a crew on scene with their hands on the hydrant to check them out every year. Does it work? We don't care how old it is, how new it is, what the paint condition looks like. Can we open it up and when we turn the nut at the top will we get water out of it? It's a couple hundred gallons worth of water pouring out of the hydrant.  I would argue that whatever the city spends is well worth it for peace of mind to know that that critical piece of public safety infrastructure is in good working order.


Hello everyone and welcome to another episode of Code Emporium where we are now going through some code on fraud prediction. So I've created a video on this a couple of months ago in the past where I went mostly through the theory of like how chargebacks are created and some of the nitty gritty details but at a theoretical level of what happens when customers like file for chargebacks, what happens when they file for claims. Now let's actually use machine learning in order to predict whether or not a customer will create a claim or try to file for a chargeback at the time that they make the purchase itself. So transaction fraud it's a pretty common problem that people tend to tackle when dealing with machine learning especially from the get go. I do know that a lot of people tend to tackle it from the perspective of anomaly detection or treated as an unsupervised problem as such. But in this approach we're actually going to look at a typical supervised approach of satisfying and trying to solve for predicting transaction fraud at the time of purchase. So with that let's just get started. So right now we have a pretty solid concrete problem definition. Given past transactions try to determine if the current transaction is fraudulent. Right. And now with with the data source it's pretty cool. We have a little Kaggle data source which is massive. There's like this train CSV is like like what 300 megabytes. I'll just go through a couple of the columns here so that we know what data we're looking at. We have credit card number pretty pretty nice all of this by the way is synthetic data. So it's not like somebody else's credit card information is just shown on Kaggle. We have a transaction date credit card number the merchant name. What was the item that was purchased and amount amount is like the price of that item followed by some user details. And this is just 10 rows of the 40 or 10 columns of the 46 actual columns that we have to work with.  So it's a binary variable right here that I could I could check as well. And that would be mostly our label for this data. So now interestingly all of this data was generated kind of by this but there's like a little repository here from which they got the data. And this person or rather used Faker which is a Python library to generate fake data. And you can kind of see you know certain certain fields just being populated with with just fake data over here. So be sure to check that out if you're really interested in just generating synthetic data. It's fairly useful I think when dealing with problems in data science where you know you're not able to actually use real data from some real database. So that's one stuff. All right. So now coming to the to the actual like looking at the data you know that data set for training is huge. But we cannot really train on those millions and millions of rows. And so what I do is I just sample 100,000 rows which is 100,000 transactions and then make use of that for like training and testing. Right. And it works just as well. So if you look at that this is transaction data I have 100,000 transactions sampled for from like beginning of 2019 to mid 2020. And there's 575 fraudulent transactions that have occurred, which is pretty reasonable kind of realistic data right here that we got. So let's work with this. Now in order to identify I want to kind of make use of regression right so the idea is to predict whether or not a person has committed fraud or at present. And what we want to do is we want to look at all the past historical data and the historical behavior of that particular customer. So we got to make sure that you know we're able to get all of the data with just like a single identification. In this case I could just use the credit card ID as the unique user identification. I'm doing this check here just to make sure that you know one unique user is mapped to one unique credit card just to make sure you know like there may be some cases where a user has multiple credit cards. Or like credit card might be tied to multiple users if you know users live in the same household. But it looks like none of those complications exist and we don't need to resolve those entities right here. And it's pretty cut and dry. So I just use the credit card number as the identification. But this is something that you would really need to look into when you are dealing with real data. So let's go to feature engineering right now. The thing is with these labels that you see like that I talked about the binary label of is fake and is fraud and is not fraud.  Unless a customer actually comes back to you and says hey I see like a transaction that was made on my card you know two weeks ago. Can you like deal with this because that was a fraudulent transaction it didn't occur and it's only then that you get a label right there. And so you would ideally what you would need to do in order to get this data set is to wait for a certain amount of time. And then say okay after this certain time you can say that 97% of people tend to either claim that their transaction was fraudulent or not. And it's only then that you actually have the labels. So let's say that you know I'm in a company right now like that has this kind of data and I don't have access to the historical data in this particular context. But if I did and in a real company I would what I would want to do is like plot some graph that looks like this. So the x-axis is the days until the fraudulent claim and the y-axis is what percentage of the total claims came in you know before the said day on the x-axis. So in this case I see like a bunch of people start filing claims you know until like maybe 60, 70 days out. But then at 90 days it really starts flattening out which means that after 90 days you can see it's almost 100% like 98% maybe or something like that. So that means 98% of the time that a claim is filed it would have come within the first 90 days. So we can kind of use that as a label when actually creating our data set which you will see when I introduce you to a SQL file that is used to create the training set. But before then before you actually write any of the SQL you want to kind of take a doc out and then just think about like what are the factors that would affect whether a transaction is fraudulent or not fraudulent. And I've kind of explained this in the other video but basically you want to do this exercise so that you have like okay what is the criteria of you know determining whether fraudulent or not fraudulent. How do you think what is your hunch on how the behavior is and then go about actually analyzing the data to verify those hunches. So in this case let's say the first thing that comes to mind what is the indicator of fraudulent behavior. Well has this person have has this how many like trends past transactions were both fraudulent and non-fraudulent by this customer. I would think that more fraudulent past behavior indicates like this may be another fraudulent transaction for example and then I would go and verify that with the data. And the second I would do the same for the merchants we have merchant data remember so we can try to see if okay like let's see that if this merchant is legit as well. Sometimes there may be like coercion between the buyer and the merchant they might be working together to dupe the company we don't know and so we want to also validate this. The next is purchase amount I would think that you know for like larger purchases like maybe products of like $10,000 you might see that like fraudulent transactions do tend to occur a little more. But again you would need to verify this then location so with location it's I'm mostly doing location because you know and typically e-commerce companies you know when you do a delivery service with like Amazon. Or UPS whatever like UPS right so the chances are that like if you live in a shady area you the customer might just file a claim that their package has been stolen. But even though it's not like fraudulent but that's only because like they live in a shady area and that's kind of why they're doing it. And so that's why I've added this as an indicator so if they so it would you know location you can kind of pass in as like a categorical variable to your to your model right. Now I want to take all of this information there might be so much more that we can probably you know scrimmage from this kid data. But let's just take this information and then try to create our data set for training. And so I have this like base dot SQL right queries slash base dot SQL so let's open that file and it looks like this. So from the get go it's a bunch of CTEs that you know you can use to which I strongly recommend that if you don't really have a good grasp on SQL. I highly recommend you learn about how you know you should be writing SQL in general with common table expressions so that it just becomes easier to see rather than like nested queries. So let's just look at this first CTE just getting information from the transaction basically. It's just the entire like I'm just getting the data you know just what whatever I have in my data frame which is DF all of this by the way is being. I'm able to write SQL here because of pandas SQL. So it's easy for me to just write SQL rather than like operating on pandas data frame with data frame operations which to me is a lot harder than just writing native SQL. Hence I'm using it. Okay, so now you have this other CTE for past transactions and the goal for me to do for me here is like for every single user ID which basically is credit card number. I want to get the total number of past transactions that have occurred and also the number of and also like if there's nothing it would just be zero or for example. And what was the average price of those transactions. And remember I'm only considering transactions that happened over three months ago because it's only at that point that would actually have labels and I don't want to use anything beyond that three month mark like from like the last three months from today if I wanted to evaluate because my label doesn't exist for the if it was fraudulent right. And so I get you know all this past information right here. Now, I'm doing this now this is just like past transaction information and I write the same CTE for fraudulent just to determine like how many cases were number of transactions that were fraudulent in the past. And the only difference between the first and the second CTE is this that fraudulent transaction that is fraud is equal to one. So it only this so this counter only have just the fraudulent transaction count. And I do the exact same thing for these two CTE's but on the merchant side. So how many transactions that I have and how many of them were fraudulent right. And then I combine all of that together in just this final sequel expression where I'm just doing a bunch of left joins on the original transactions. And in this like you can see that I am also saying okay if the if the location really isn't if if the location isn't known or it's like it's missing. You want to just populate it with UNK which is unknown. And also like if you know if there are no transactions at all sometimes it will be null there too. And I want that I want that to actually be true because no past transactions is true in this case. And I think you can infer the same from all of these all of the other functions here. Now obviously I'm like you cannot do a divide by zero like I wanted to do fraud rate and I wanted to see if this would be like a good feature. I cannot divide by zero if then if there are no transactions that the user is made and this is the first transaction this will throw a divide by zero error. And that's why I'm putting I'm wrapping this in a case when statement and I'm doing that same for like the merchant fraud rate as well. So that's like a really quick overview of like how the data set is constructed. And remember we are only using data until three months ago because that is the data for which we have like an accurate label beyond three months. We just don't have labels right hope that makes sense. And I hope you get that right. So now once you actually construct that data the result of that here is like a single a line of like the features for a particular transaction. So the label was zero so there was no even three months later there was no there was no claim that was made that this was a fraudulent transaction by the customer right. And yeah that's it. Now with location you see 904 I if you see that that was I use the zip zone prefix so essentially just extracting the first three digits of the zip code. These if you extract too much then that means that like it's just too too many categorical features if it's too little it's going to be less important of a feature because zip code is actually indicative of regions. It's pretty important it's pretty cool to know of how zip zones are created. Now creating the model right. So first of all I have this function for creating for under sampling. You'll see this later when I when I use it here. Let me actually just go through this a little bit first. So I have a bunch of categorical and numerical features that I think are that I've just like manually put into this. And from here I am splitting the test set and the train set in a tennis to one ratio. So there's like 100,000 samples 90,000 will be trained 10,000 will be test and I'm not I'm choosing not to shuffle so that you know we're not predicting on data that happened anytime before the training set data. If you shuffle it you might suffer from like data leakage issues which is pretty bad and a very common mistake among you know when you're starting out with machine learning. But the thing is that you don't want to train and you don't want to literally train on this directly because something that we're seeing here is data imbalances. There's only like 500 or so fraudulent transactions right but there's like 90,000 90 or 100,000 of like total transactions. This great imbalance will mean that if the model just keeps on spewing out non fraudulent non fraudulent for every single thing. So just like a death return false then your model will technically perform super well now precision. Obviously the precision is like near the zero but I'm just saying like in general your accuracy would be pretty high and you don't want you want your model to be able to pick up on these little anomalies. And so in order to cater to that I created this function called under sample which will basically under sample the train set. So if I only have 500 of these samples in the like positive labels it will make sure that the ratio of negative to positive is at most just four. So if I 500 that means I will only have 2000 of the negative samples and that's what I'm kind of doing here where I'm just sampling just to make sure that we take care of the data imbalance situation. So we're technically under sampling the the data set from the from the negative label because there's just so many of them. I hope this pace isn't too fast but I'm just trying to get through all these ideas and you can probably like look through the notebook and understand with more details just by looking in line by line at the code and probably just Googling certain things too because I'm hoping that it's not too out of the box. So right now for categorical features where this is like a typical pipeline structure that I do encourage everybody to learn of how like when they create models. It's a great way to pipe in from pre processing all the way to model classification. So the way I'm doing this is like all the categorical variables are going to be pre processed in this way they're going to be imputed by simple imputer from scikit learn and we're going to impute it with the value of negative one. And then I'm going to do some ordinal encoding which will basically start ordering all the categorical variables with integer values and for the numeric variables. I'm just imputing it with the there's no there's no parameter so it just takes the mean of the column value and just imputes or rather fills the values that are in a into that cell. And then what we're doing is creating a cat boost classifier. So cat boost very fun. We're going to be creating that classifier and then piping all of our pre processed data into this classifier and then fitting the model on the under sampled train data. And so you can see well over like what one 1000 iterations the the loss is definitely decreasing the model is learning. Right now. And as far as evaluation is concerned, you know because if there's such like a huge data imbalance, we want to make sure that we are taking into account both precision and recall correctly. So instead of using the typical use ROC AC curve we're using a precision recall AC curve because precision recall are super important to consider when you're dealing with data imbalances. Right. And so I'm kind of taking all of this into into account over here. And we have trained and test metrics. Yeah, I'm just evaluating that and lookie here. We have pretty good we're actually doing pretty good with with our metrics over here. So I mean like even the AC ROC is like in the 80% I mean that could be reasonable depending on what situation that you're you're dealing with. And then as far as the confusion matrix is concerned that this is I think like super important because it kind of tells you the breakdown of how many fraudulent transactions be predicted. How many fraudulent transactions were actually there and then trying to see how many we got right. So we know let's just look at the test set because that's what we're concerned with. There's like if you sum these up there's like 10,000 transactions or so right now if you look at it there's 58 cases where you know they were actually fraudulent transactions these 58 they were actually fraud. But we end we actually predicted fraudulent which is great. Now these are five cases where that was actually fraud but we didn't predict them fraudulent so we missed these which is bad. But overall for the 63 cases that were fraudulent we picked up 58 of them which is pretty good pretty good actually I guess yeah. And then there's 124 cases that we predicted were fraudulent but weren't actually fraudulent. So these are like you know our model just gave false positives to which is which is fine it seems like a low reasonable number. And these are just the typical true negatives where you know we just normal transactions that just pass through which is good right. So overall it looks like our model is already performing pretty good. That's great but the thing is right now if somebody comes up to me like a stakeholder and says okay this is great and all you have a model but like. What what were the most important factors that are contributing to this model like what determines a fraudulent transaction the most. And to them well we have a model interpretability using Shapley values. So SHAP is it's a it's a library that's used for visualizing these you know the importance of certain features in models. Now I've made an entire video on this but essentially uses game theory in order to it's like all these features are now competing in order to see like okay if the sample is fraudulent. What exactly is making it fraudulent there is some some amount of space that is allocated to each feature. So the total of them should be like okay we have this much space what is actually making it fraudulent this divergence what's causing that divergence. And so all of your features would fit into this with different points in different ratios and it would be scored proportionally to like how effective it is. And now in this case it's saying that well the price is the is by far the most important feature. So it doesn't give any sense of direction but my hunch is like okay typically if it's a higher price chances are that it's most likely like okay you got to be careful of this one right. And then after that is no merchant fraudulent past transactions so if a merchant has had a fraudulent past transactions you know okay you got to be careful of this. And interestingly even category so it's like depending on the item that is also being purchased it seems to have a pretty high weight. So when actually looking at that I think I did that analysis a little later let me just hop to this. So category was interesting because it's like people who bought shopping nets and grocery and whatever these are like they actually had a higher tendency of actually filing for a claim or you know making these fraudulent transactions. I jumped ahead of myself a little bit but let's just continue here. I wanted to also look at there you know SHAP is a great library for visualizing these things you can visualize it at like the overall data set level of feature importance or even at like the transaction level. So let's say that this is an example transaction where you know we predicted the model there was not fraud and the predicted the prediction was also not fraud. So why exactly did the model make the prediction in the way that we did given these features. Well we have like so here is like the entire gist of like you know these each additional feature in their contribution blue and downwards just mean that it's decreasing the probability. Red and upward means that it's increasing the probability of being detected as fraudulent. So it's saying that okay the biggest factor is the price is super cheap it's like 6.84. That's probably why and there is never there is no merchant fraudulent past transaction. So the merchants never made any fraudulent past transactions which is also a huge indicator. And then there's also all these other things that are huge indicators and that's why it's something it's it's kind of pushing it down right. And that's also why like it's pretty low. Next is let's just take another look at another example but this is a fraudulent sample. It's actually fraudulent and our model correctly predicted it as being fraudulent but why was it being predicted as fraudulent. So it looks like the price is over a thousand bucks whatever this item was. Yeah this shopping net it was over a thousand bucks and that's really contributing to the fact that okay you got to look into this this might be fraudulent. But then there's also the category is equal 11 which is surprising this is like the second most important factor. And category 11 is essentially shopping net. And like I said before it's when I just tried to look at that I thought that was super interesting. But like people who tend to purchase shopping nets the fraudulent transactions for those is actually the highest among all other types of items that are being purchased. Which is a really fun fact that you can see in the data and you could probably pick up on so many other samples just by looking at them too. So that's kind of all I got for this entire notebook but there are certain other questions that I would answer in addition to these. Like one of them is like the actual modern model interpretability like I mentioned like this this shop graph right here. It doesn't give the directional importance like I know that price really has a pretty strong indicator of like whether something is fraudulent or not. But like what does that mean what is that dependence like is it higher the price is a lower the price. What is it my hunch is obviously higher the price but you can figure this out and also make sure that that is the case by plotting partial dependency plots. So it'll be partial dependency plots will be plots of the actual feature value versus the versus the actual regressed or whatever this categorical value. And just trying to see like how how that probability would vary just depending on varying this one feature keeping out all the other features as constant. So try to plot this partial dependency plots and see what you get. It'll be pretty interesting to also verify our hunches just to make sure that the model is performing in a way that you would think it would. And that is super important when you're dealing with data science in the real world. So partial dependency plots very fun. Another thing that you can look at is try to use model interpretation on you know Shatley values can be used for on any model. I just use it on CatBoost here but you can use it on XGBoost even neural networks whatever you want. So you can try even replacing this model and trying to see you know how what what changes in the model interpretability and also the performance right here. Like does this graph change by much if so which features change. And you can check that out try to try to replace the CatBoost model put something else in and I think it's going to be it's not going to be too hard because we have this like pipeline architecture that we set up. So essentially all you need to do is just like you just need to make a couple of changes here and everything else should like remain the same right. So plug and play for you know these this like machine learning pipeline makes it super simple and that's why machine learning pipelines are very fun and very important. So I encourage you to try that out if not if you can't if you get you know stuck on a roadblock I've created an entire video and also notebook explaining shop and also interpretation of Shatley values. All over here in this new notebook and I encourage you to check it out as well I have an entire video on that too. So that's kind of all I have today again you can treat fraud detection it's in fraud prediction I should say as like a problem of regression or rather classification rather than. You know some separate anomaly detection ESC kind of problem and it's not too hard to do but it is a little different in terms of data collection because we just don't have the labels up front. So I hope this really helps understand a really common problem that I've seen in in at least in Kaggle and in just getting up to speed and machine learning. Hope you enjoyed everything here learn something new and I will see you all in the next one. Yes, I'll see you all in the next one. Bye bye.


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rward with suggestions we should be open-minded to stakeholders and we should be open-minded now we'll be open-minded to other political parties that come forward with suggestions the member is right to make reference to timing and timescales that work is on-going and is an immediate I would of course endeavour to keep Parliament updated I would hope that I'd be able to give you if not a definitive at least a a steer on the direction that the Government and partners were going towards before Christmas recess for example and I'd be happy to of course come to the Parliament and indeed the committee to provide that update Is that your questions conciliator? Yeah that would be good to get an update I wonder if I could pin you down just a little bit further cabinet secretary given there was only one option on the table then and to be honest I think that the Scottish Government was very intransigent with this just going with one option ignoring all the others Can I ask you specifically is the administrative devolution option that BTE, PA and the BTE P came up with is that on the table as an interim option and is the statutory devolved model of governance and accountability with BTP A retaining responsibility for railway policing in Scotland also on the table So I think I answered those my previous answer while they may remain on the table I would have some concerns because of the shared accountability so I think they don't quite deliver that or go far enough in terms of the spirit of the Smith commission the spirit of the Smith commission such that this Parliament and it should be for this Parliament to have powers over railway policing but also accountability in terms of the models that she's mentioned the UK wide governance structures and accountability structures would give me some cause for concern not just because of the Smith commission but also the potential confusion that may well exist so while I say that nothing is off the table I have some reservations and I'll be open about those reservations but if I can be convinced and persuaded otherwise I'm genuinely going into this with as much of an open mind as I possibly can The difficulty of being so open minded I think from the committee's point of view this morning Cabinet Secretary we know clear idea exactly what is on the table and if there are problems with these models what the problems could you flash out some of that and it may be that you would like to reflect on this and write to the committee with more specific reasons why the administrative model of devolution for example doesn't quite seem to be one that you can say yes I'll certainly put that as in as a possibility at this stage and the same with the statutory devolved model of governance and again development Yes indeed and if the convener would mind it would be my preference to get the stakeholders together to do some of this work to determine which path we're going to go down without prejudging so I'm doing my best not to prejudge you you've asked me a question on if I have any reservations on those particular models I've expressed where I have those reservations but I'm not completely discounting them and while of course I have every right to ask us for further thoughts and reflect on that of course I would do that if that is on the insistence of yourself and the committee but I would really be reluctant to do anything that would look like I'm prejudging what will be an important discussion with the various stakeholders including BTPA, BTPA, BTPAF and I understand cabinet secretary there's a balance to be struck but a little bit more data I think would be helpful and can you tell the committee today when this consultation is starting how long you think it's going to take? The conversations are are already beginning and I'm looking to meet with stakeholders very soon on that and again in my response to Sean Robison the timeline would hopefully be able to come back to committee and indeed back to parliament certainly before Christmas recess to give you hopefully a definitive on the option that's been agreed by all partners now we may not get to that point and of course I'll keep you updated on that but I'm trying to strike a balance between understanding that there is absolutely a time imperative on this but also making sure that we absolutely get to the best interim arrangement that's possible okay supplementary Daniel and then photo thank you I'm just wondering to what extent there's a time constraint in terms of finding a solution for this given that railway policing is both delivered and funded in accordance with PSA agreements between rail operators and the British Transport Police and therefore there's a natural contract cycle that that will I mean I'm just wondering whether or not that provides a window of opportunity which requires to be met yeah and there may well be I mean there's a the contracts are done on a four-yearly cycle basis but as I said my answer to the convener we are not wasting time on getting on with these conversations that have to be had and I think a challenging time scale of settling on an option before Christmas recess where possible so I think the member's right to to raise the the time challenge that we have and the pressure that we have in relation to the timing but nonetheless I have confidence that we'll get into a position to be able to give interim options hopefully by the Christmas recess and pursue them and move along with them as I said at a pace so is the cabinet secretary aware when that four-year cycle is up and when they're due to renew the PSAs? I'm not entirely sure I don't know whether Donna has information on that I don't know I don't have that information just now I don't have that information neither at the top of my head but certainly we have arrangements that are in place that have worked well for the railway industry between the railway industry and BTB as things stand and if it was needed that they would come to to arrangements to agreements then they'd be able to do that but as I say I don't think it's such a time imperative that should we get to an option of the direction of travel we want to go by Christmas recess I think that that would stand us in good enough stead but if you missed that renewal point you need agreement from the operators to bring in new agreements If we are creating new arrangements we will have to negotiate with the railway operators anyway and the break points are obviously set up for the arrangements with BTPA so if arrangements are with another body then it would be a new arrangement anyway so we would need to enter into discussions about when that would start the structure the arrangements around that so I think while the break points are a useful timing to consider it wouldn't preclude us doing that work at any other time but that would be a matter for negotiation with the railway operators at the time if we were to do that You wrote to the committee with the renewal dates Yes Thank you Any other questions here? Fulton Thanks, convener Can I just express my sheer disappointment with the cabinet secretary on today's news in the process we are now going through but also to give credit for taking the advice of Police Scotland which is what you and your predecessor always said would be the case if they raised any concerns If somebody sat in this committee and spoke in the debate I was convinced as was the majority of Parliament that full integration was the best move but there was one particular specific area which you mentioned yourself cabinet secretary which struck out and that was the ability of Police Scotland to train all officers in the railway area and allow then fast response to various situations that might arise Can I get some reassurance that that won't be scrapped or lost in this interim period and do Police Scotland have any plans to continue on with that training facility? I don't know whether that would be part of their plan because my understanding was that that would be done upon full integration but it again you'll forgive me I can't quite from the top of my head a pinpoint whether that was the case or not and again I might refer back to Don on this It does though speak to the point I'm making around full integration and keeping it under review that the Government just because we have taken the steps and taken the advice of Police Scotland at this stage around not being able to give a definitive date for full integration doesn't mean that we no longer believe that there are benefits of full integration we do and I've spoken to some of those around seamless policing and single command structures and training enhanced training and so on and so forth so we still believe that that could be done but clearly it would be foolish of us not to heed Police Scotland's advice I don't know whether Dona has further information on the training aspect of it because it was going to be an additional a couple of weeks kind of bolted on to the end of training for Police recruits but I don't know whether that will be happy and that was one of the work streams that was developed as part of the programme planning so Police Scotland did a fair bit of work on training needs assessment both for Police Scotland officers I mean that you would get more specific information from them about that but a piece of work around training needs for all officers and also training needs for any officers who are transferring from BTP to Police Scotland so there is a piece of work which has been done that sets that out which Police Scotland could potentially share or if they were prepared to do that Finally Cabinet Secretary I'm aware that there are representatives of the BTP in the gallery in the audience today so what reassurance can you give them and assurances that their views will be fully listened to and presumably acted upon? I've been heartened by the fact that the majority of those that you mentioned if not all of them have a welcome to government getting to this position around pausing the work on full integration keeping it under review and so on but focusing very much on interim arrangements that I've also seen from them a welcome in terms of the tone we've taken in relation to bringing stakeholders together so that gives me reassurance that our message is getting out to those stakeholders and I want to engage with them as soon as possible on the number of them I have meetings in the diary already set for those that haven't we will be speaking to them I'm sure and relatively shortly so I can give them an absolute assurance I can give them an assurance as I've said previously that we absolutely value the expertise that their members have and hold and that we also understand that there's still an element of uncertainty that clearly exists until we come to those interim arrangements and potentially the long-term plan and I'm cognisant of that and you know where I can give comfort to that I'll do my best to do so but as things stand of course right now as of today the current arrangements stand for for for for BTP but clearly if we're deciding on options before the Christmas recess which I hope to do or the winter recess which I hope to do then we'll try to give as much certainty and as much information to officers and staff as we possibly can yeah just to clarify when you're consulting and you know part of looking forward is consulting with SPA Police Scotland will the representative representatives of BTE officers and staff be involved at the same level as equal partners and do you have a date when you're actually going to meet with them given how germane they are to this whole this whole issue on the process? Yes I was chatting to Nigel Goodman on my way in to committee we have a date in the diary for meeting with the British Transport Police Federation so there and that'll be a personal meeting that I'll be conducting so yes absolutely that their voices will be equal to any other stakeholder very much in this process and I look forward to hearing from them as I said I know that other stakeholders have come forward with other suggestions other potential models some of those I have some reservations but I'm happy to talk to them on those options are indeed of any new options that might come from from any other stakeholders and the date is before the winter recess the Christmas recess sorry? the date is before the Christmas recess yes the meeting date for sure and the date that I'd hoped to be able to to give you options that the partners have agreed on or settled on if we get to our kind of consensus point hopefully then I would hope to get that to you before Christmas recess also okay thank you very much that's very reassuring that concludes our line of questioning we need now to spend briefly just to allow witnesses to leave agenda item three is four it's time flasic agenda item four is consideration of a negative instrument share of court fees amendment order 2018 SSI 2018 oblique 194 I refer members to paper 3 which is a note by the clerk it also includes the Scottish Government's response to a concern raised by the committee that the original instrument had contained an error which allowed certain exemptions for the commissory fees do members have any comments no comments I think it was good to raise this and we are satisfied with the explanation is the committee therefore agreed that does not wish to make any recommendation in relation to this instrument agreed thank you agenda item five is an appointment of a European Union reporter the committee has to nominate a member to act as the European reporter and I refer members to paper four which is a note by the clerk and paragraph five of that paper outlines the role of the EU reporter and um can I have a nomination John Finnie in MacArthur thank you are there any other nominations that being the case then I'm delighted to tell you Liam you are the the EU reporter for the justice committee thank you very much thank you um again agenda item six is a feedback report for the meeting of the justice subcommittee and policing on 13th of September following the verbal report there will be an opportunity for brief comments or questions and I refer members to paper five which is a note by the clerk and ask John Finnie to provide this feedback excuse me thank you convener you're rightly say that the last meeting was on the 13th of September last week and on that occasion we took evidence from Police Scotland's regarding the proposed use of digital device triage systems now these are more commonly referred to as cyber chaos um as well as Police Scotland we had the Scottish human rights commission and the information commissioner's office provide us with evidence and that evidence focus on the requirements and safeguards necessary prior to Police Scotland using this technology throughout Scotland to interrogate the mobile phones of witnesses and suspects and of course the committee previously expects concern that a trial had taken place without any of these protections we welcome the fact that Police Scotland has established two groups to consider and agree the human rights and equality impact assessments data security storage and retention policies and the public information provided prior to the introduction and the training of officers now we heard from the Scottish human rights commission the significant concerns they had about the draft versions of the human rights and equality impact assessments and again their concerns about trials being undertaken without any being underpinned by any such assessments a pressing concern expressed both by the human rights commission and the information commissioner's office was about the legality of Police Scotland's seizing and interrogating the mobile phones of people accused of a crime or those who had witnessed a crime and Police Scotland confirmed that if there is no legal basis for them to do so then the rollout of cybercares currently planned for later this year will not proceed and this is an issue which the subcommittee will return to once the assessment policies, procedures and guidelines have been finalised and are public available and falls into some of the on-going scrutiny arrangements we have with the inspector regarding related matters and thank you for that comprehensive report are there any comments I'll just say I think it was an excellent session and there are certainly issues arising from that that need to be picked up and addressed so I think it was a good session convener right if there are no questions that concludes our 23rd meeting of 2018 our next meeting will be Tuesday 25th of September when we will continue our evidence taking on post-legislative scrutiny of the fire police and fire reform Scotland Act 2012 I'll now close this meeting sorry can I just no no no no it's closed


time here for more systems and we're going to talk about direct attach copper some fiber modules and why these are a better fit than your standard twisted pair cables that you want to run when you're running them inside of your network stack where your data center or just in the rack in general unless there's a couple long distance runs and you may want to use these fiber modules now all this is coming out of to focus in on these cables in particular and their use cases because I did a video breaking down what cables are used where but of course there's a lot of expanded information I wanted to add but was out of scope of that other video that I'll leave link down below to we dive into when exactly we do use these and why we use these and latency and speed is a big thing power usage well someone's going to point out that these can go 10 gig and this can go 10 gig so speed versus the latency that's where the challenge really comes in of course the efficiency of using these so they will go the same speed but the latency is going to make an overall better experience for using them and there's some real technical reasons why and we'll dive into those details here before we do if you'd like to learn more about me and my company head over to Lawrence systems dot com if you'd like to hire a short project including network consulting there's a hires button right at the top if you want to support this channel other ways there's affiliate links down below to get you deals and discounts on products and services we talk about them this channel and we'll start right here with 10G base T versus SFP versus DAC which is used for your data center despite this being from November of 2015 and it being currently August of 2021 this still holds up and this is the latency debate but a very relevant one latency and power are going to be two really big factors that play into why you want to use these cables now this is the relevant sentence right here the five standard specifies 2.6 microseconds for the transmit receive pair and the size of the block requires a latency to be less than two microseconds SFP uses simplified electronics without encoding and is typical latency around 300 nanoseconds per link and then they have a chart that breaks that down now for the simplified version the electronics it takes to take these twisted pairs and this is a cat six cable and the shielding goes up with the higher grade cables all the way up to your cat eight having a lot of extra shielding around here to eliminate any potential interference what they're doing is they have a series of electronics that does signaling down this and we twist the pairs around each other and put insulation on them to prevent the degradation or interference with that signal that is a lot of electronics that has to do a bunch of differential calculations to make sure that the data on one end is getting through to the data on the other end and every old bits come out exactly perfect they're never perfect but the electronics makes the perception that they're perfect and the data then flows with your direct attached copper simplified electronics means they're not doing any of those differentials so without those differentials happen to be done although we lose the ability to go over distance we save on latency because there's not that extra step that something has to go through of turning it into the type of signaling that this needs and breaking it back down to a simple signal on the other side by eliminating the extra components we've simplified the connection we've lowered the amount of power the other advantage and it does take a significant not even poe just the amount of power it takes to do that signaling you push this across and this allows for a less expensive card and less expensive switches both in power expense and in actual cost because there's less electronics needed to operate these to get the data to where it needs to be all right now let's dive a little deeper but when I see deeper I really just mean in choosing the different type of DAC versus AOC cables because this came up when people said well you've mentioned DAC but you didn't specifically see AOC I kind of look at them the same but I know they're different they will look and present mostly the same the direct attached cable is compromised of a twin X copper cable terminated with in the different SFP versions three different types here passive copper active copper active optical cable and these are when you use what so passive DAC cable like the short one I had less than seven meters is going to be just twin X copper cable uses very small amount of wattage and kind of the uses top of rack tour not like the tour protocol but top of rack is what that stands for or your adjacent racks same thing here you have tour and adjacent racks again for these because it depends on how far those adjacent racks are so if they're adjacent racks are pretty much next to each other you could connect these your active deck cables a little bit more expensive but go up to seven to 15 meters active optical cables active out cables I don't have one here for presentation but essentially what an AOC cable is is your fiber module and the fiber all mated together in one and what that allows you to do is not have to worry about whether or not someone would have any loose connections or any dirt getting into connections or buying the cable and the module and plugging them all in together it comes as a fused unit that looks the same as far as these DAC cables go but happens to be a little bit longer and of course the cable between being fiber means it's pretty thin cable to run and of course power consumption is low on all these they have the wattage listed transmission distance back to that and overall cost now EMI immunity electromagnetic netic interference refers to disturbance generated by an external source that will affect electrical circuit this is something you deal with a lot the active optical cable contains optical which means yeah no big problems with EMI you can run it across something like let's say you have some type of the high voltage coming in a room on the other side and or in between where you want these two cables to be and running a fiber optic cable across here whether it be a standard fiber optic or you're running one of these AOCs you're going to eliminate the problems that you have with that and they have a few more examples I'll be leaving links all this and you know here's your top of rack switch and where you may want these and the servers and the different cables you'll have in between now I wanted to include these in here because these are some of the newer ones is the 25 g connectors now one thing about them they're the same physical plug of SFP so SFP one gig SFP plus 10 gig SFP 28 25 gig okay I didn't name it but right here 25 gig is SFP 28 physically the same here something cool that they've done here is the dual rate transceiver solution to the 10 25 upgrade path I thought this was kind of cool and it keeps with some of the backwards compatibility let's actually show it in action rather than just read stuff that says it works let's actually show you how it works what we have here are two different unify switches this is just a 10 g switch this is the unify aggregation switch that offers 25 gig connectivity and what we did here was plug in and the 25 gig port which is actually unplugged right now so I'll plug that back in so I was playing with it there we go it should light up here in a second but in order to get this to work we took and you can see here we have a 25 gig connector plugged into a 10 gig port the way the compatibility works this does include with some of the fiber modules that they have produced the 25 gig SFP 28 cables and fiber modules are both backwards compatible with SFP plus ports but you do have to force negotiate them down for example right now this is showing connected at 10 gig because we overrode the settings and turned off auto detection and said force it to 10 if we go to 25 it fails and if we set it on auto I'm 99% sure that's going to fail and give it a second provision it's going to think for a second and blink I think it blinks back if we're trying to negotiate and it doesn't yeah and yep it's failing kind of get the idea but when you negotiate them yeah we'll turn them back on to negotiate back down you are able to keep that compatibility so if we go here well profile override turn off auto negotiation force it down to 10 gig that works and we did the same thing we just plugged one of the fiber modules in so if you actually see that the fiber module which is in this port right here is won't know if that's the yeah there we go we have an SFP 28 plugged in there and it'll negotiate down so the negotiation down does work and we have it in here as well you can see that these are both marked to be the SFP 28 SFP 28 and this is what's important to consider you can take if you have ports that are SFP and you can use an SFP plus cable now you can't do the opposite you can't take an SFP cable and plug it into an SFP plus port well physically plug in but it won't negotiate up so you want to get the SFP plus cables or SFP 28 cables like they have here from FS.com that I'm holding because these you can force to a down speed but you can't force them up now this is good if you are dealing with some interoperability of old legacy systems and for example this has 28 ports on it that are SFP plus 10 gig ports but what if we have all these 10 gig switches a couple of them are only one gig but they still are fiber connected to a far end of a building somewhere that means you would be able to negotiate down the speed and be able to keep those in there until you got around to upgrading them and then the way that we work with the ones here from FS.com are these modules that are SFP 28s are able to negotiate down to 10 once again if you start building out the head end of your network first but you still have some further way devices that are still at 10 gig you can negotiate these 28 SFP 28s down to 20 from 25 gig over down to that that 28 and 25 gig is keep messing me up here I don't know why they need to why they just call them SFP 25 wouldn't that be easier I didn't make the naming schemes up but you can see the negotiated pass when you force negotiate them and that's something in general it's not like when you're dealing with the standard you know cat 6 on up cables you will sometimes have to set the negotiated speeds when you're using some of the DAC but the way it works with the cards the way it works with here is that lower latency application more cost effective less power consumption and more budget friendly overall so that's one of the reasons these are popular and they come in a variety of different sizes so you can usually find one pre application but of course they're not quite as short as normal patch cables and there's not patch panels for these so if you're trying to make a really nice looking you know mount everything in there and make it look really pretty back and forth it's a little bit harder with the DAC cable so that is kind of a disadvantage of them but I mean some velcro you can deal do some cable management it's not going to be as pretty as the patch cables but it's still going to be a great application a great way to use these so hopefully that educated you a little bit on some of these things I'll be leaving links to these articles where you can dive deeper in there including a video I did before based on this research from arista labs here and talking about copper is faster than fiber there's actually some other details if you want to dive deep again I've done a video on this before and it always opens up a lot of debates but they do talk about some of the different multi mode fibers and yes if you're wondering and I will leave with this who may have seen the orange fibers sitting here if you are curious if there's speed limits to connecting the fiber or two yeah I may do a different video all together on fiber but just look up the om ratings on fiber and you can find that pretty readily and learn that yes there are speed limits to the fiber connections as well but that'll be a separate video I'll do later I just wanted to get this one out of the way before I did some of this 25 gigs projects that I'm working on so if I have reviewed this switch in the future which will be soon the link will be down below if I haven't reviewed it yet that link will be missing but yes this is the unify aggregation switch that we've been doing testing with so that's a future video coming future now but if you've watched this in a future that link made me down below so all depends on when you're watching this all right Tom Lawrence here and you can find me over in the forum so we can dive deeper into this and leave your arguments and debates below and uh looking forward to hear from you thanks and thank you for making it to the end of this video if you enjoyed this content please give it a thumbs up if you like to see more content from this channel hit the subscribe button and the bell icon to hire a sure project head over to LawrenceSystems.com and click on the highest button right at the top to help this channel out in other ways there's a join button here for youtube and a patreon page where your support is greatly appreciated for deals discounts and offers check out our affiliate links in the descriptions of all of our videos including a link to our shirt store where we have a wide variety of shirts and new designs come out well randomly so check back frequently and finally our forums forums.lorencsystems.com is where you can have a more in-depth discussion about this video and other tech topics covered on this channel thank you again and we look forward to hearing from you in the meantime check out some of our other videos


So you want to use SQL Server to break into tech? Well, you wish to write video. Let me explain This video was brought to you by DigiLink Academy You're number one source to learning programming fast and get to that six-figure salary you desire. Our third day project course includes our JavaScript front-end projects, our Python back-end projects, our SQL database projects and much much more So go ahead and click the link below to our free 7-step guide so that you can start reaching your programming goals today I'll see you guys in the course So most of you guys are in three boats You're trying to be coming to developer you're struggling You haven't got that opportunity to break it to tech yet or you're already in tech in a struggling job or a dating job And you haven't got that opportunity to be a Python developer Or you a Python developer may be a junior or standard and you really want to take your career to the next level and All you guys are asking the same question. Is Python worth it in 2024? And the quick answer is yes But I'm gonna give you the pros and cons which way you need to go and what you need to do to actually get started as a Python developer and it's gonna really give you guys context or where you spend your time at and don't spend time Just spinning your wheels and wasting all your time. So Before we get started guys go ahead and comment below about your situation What of the three you're at? What are you doing to get started? What are you struggling with so that we can help you guys below? So go ahead and put your details in the comment section and let's start a conversation So let's start with the first one somebody who just really getting started as a developer Interested in becoming a developer, but haven't yet was able to break into tech Well, Python give you a lot of an opportunity especially in 2024 A lot of you guys may feel like AI and all these other tools are gonna come in and take your job And yes, that is the case in some instances, but you can position yourself to be a problem-solving Not just a coding monkey and you're gonna always get the edge over AI guys, especially when you are in a solution or in it Industry and you know what you need to do to really take your software development skills to the next level and I'll give you guys a lot of that later on in the video Secondly, you guys who are in tech who's you're struggling a lot of this is just because of your reputation of your current job because Quite frankly just listen to me here quite frankly if somebody saw you as a valuable IT professional and You have done a good job They will give you an opportunity to be a software developer if you have demonstrated you can solve problems And that's your problem reputation If somebody haven't given you that opportunity yet, they may feel like you can't do it So either one or two things you either get your skills up showcase your skills And maybe they give you an opportunity more than likely more than likely You're probably gonna have to go get another job because especially been on a job three four or five six years Let's just say you've been working to support all that time You probably got the reputation of being in support and you can still leverage of Python But you have to make sure you actually go to another job But I'm gonna give you some hints and some tips to actually get you started number three.  You're just in a dead-end job You're not working on good projects or you're struggling to really take it up a notch Maybe become a lead Python developer a senior Python developer even in the leadership role and you're in a standard Maybe join your standard role. Well, you're in the right spot. You're doing pretty good You just got to work on better projects. Maybe the company you're in Maybe they're stagnant. They're just mature in a place where they're not willing to take on new projects, which is okay maybe you can convince them to work on new stuff and Maybe you can convince them or Display hey these this is what my competitors are doing or our competitors are doing Maybe we can do something along those lines Maybe talk with the leadership team and all that to kind of get some kind of Direction going on new projects and if and if They decide hey ride or a paid developer We're not interested in moving more forward any of these new projects is Made time to look at other options as a job But in all three cases guys You have to really know how to leverage your current skills and be able to communicate how you can solve these problems Act you execute on solving the problem as well I can't go into everything in this video like I was saying number one the person number one who's a aspiring developer I have a seven-step guide links below for that guys if you haven't already We cover as far as these three areas how you can really take your career to the next level with Python Number one as an aspiring developer, you just got to get your foot in the door You got to showcase that you can do the work and put yourself in a position to win A lot of you guys with these generic Resumes got this generic information. It just not come across as you valuable So you got to get that squared away and in a seven-step guide we do that for you guys as well number two a lot of you guys who are Trying to you already in tech, maybe you trying to become a software developer same approach there You know, you got to be able to leave that job You got to showcase your value you've got to put yourself in a position so that you can start putting some projects together That worth more than just a calculator out all that's the same thing guys And last but not least probably the smallest group of them Existing developers who want to take your career to the next level Projects projects projects as you guys already know Projects projects projects is really gonna help and just knowing the industry knowing the industry now You're gonna really put you in a position to win guys So don't want to belabor these points too much. Just wanted to go over some pros and cons and cons of being a Python developer Let's go with pros first just to be positive first If you're looking for an opportunity to make six fish six figures the fastest without a degree Hands down one of the best options you can, you know, you got other options sells blah blah blah blah But this is technology company our technology channel We're gonna talk about Python development any development in general as a option that you can help Really get you to that six-figure salary really fast You can work in any industry you want guys for the most part every industry have software Every software needs to be improved over time to fit that business needs Hence they need a developer like you that's gonna take that software to the next level So you can basically work in any industry you want. You just got to make sure you can provide that Number three you work anywhere. I know I'm not gonna say that name of that the D's but at the end of the day Everybody's used to working for home. Most people are going back to work now But software development is still one of those careers that everybody Assumes if you're good at it, you can work from anywhere and really do what you need to do guys So that's the pros the cons and and this is no reason to scare you off I'm just putting things in context for you guys just so that you know both sides of the coin number one is the Everything's always changing guys as you can tell We're in technology technology changes quite rapidly compared to other areas compared to health care compared to legal It changes rapidly your skills get out of date real fast But again, we're talking about solving problems here Problems gonna always exist Technology is always gonna be there to solve those problems You just got to make sure your skill set and your problem of solving ability is current It's not something that's gonna turn around in a year But over the course of a couple of years, maybe five six seven years Yes, it would rapidly change on that time So just kind of stay on top of that and just be aware of the changes so that you don't get left behind Number two on the con side you do have more responsibility as a software developer Python develop development specifically You are in control of a lot of core systems in a company. You can really screw something up and You got to be aware of that responsibility to make sure you test stuff in the test environment You're not deploying code in the middle of the day when everybody on the live system so far Then so on do not screw up these people systems That's one of the reason why people can't get into development today because back in the day We used to have systems that may we don't have to break but now it's different last but not least guys You have to work off hours Unfortunately, that's how it is when the systems down you can be in Hawaii on vacation They don't have a lot of developers speth as standard companies. You got to come in But it's the end of the day guys. It's still worth it You're still gonna make more money still gonna have more freedom and flexibility so that you can really take this career to the next level So if you haven't already guys go down to the links in below and actually sign up for the seven step guide Like to subscribe to the channel guys. We got a lot of stuff for you 2024 is gonna be a good year for everybody and really put us in a position to win guys So at the end of the day, I can't cover everything on this video But we will cover it in the sad stuff guy now I could put a link here on the screen like subscribe to content now. See you guys in the next video click click click