Lately I worked on a more ambitious topic for a data science video. Graph Analytics, aka Network Analytics, is one of the more niche aspects of our craft and although I've been using it for many years, creating a video on the topic has always been daunting due to the amount of material it has. However, I managed to create a fairly succinct clip (a bit less than half an hour long) and put it out there through my publisher. You can find it on the Safari portal.

Note that you will need a subscription to Safari in order to view it in its entirety. Also, a subscription to this educational platform enables you to have access to a bunch of different material, including all of my books. Cheers!

Although I’ve always been a big fan of online videos and find many such projects entertaining to watch, I’ve never really seriously considered doing anything on YouTube. That’s despite the fact that I’m fully aware that some people are making a living on this endeavor.

First of all, YouTube has changed dramatically over the years and not for the better. Specifically, the algorithm used for featuring what’s hot on the YouTube homepage has degraded drastically, in a desperate effort to promote “fresh” content creators. In other words, if a producer doesn’t publish videos frequently, they are not promoted much by the algorithm, something that inevitably gives rise to sloppy and cheap content, created merely to satisfy that mindless algorithm. Of course many YouTube fanatics (or YouTubers as they like to call themselves) have their own channels and networks of promoting their stuff, so they get some views regardless. However, the effort it takes to build such a network and the fact that it require constant work to keep it active, makes the whole process inefficient and problematic in many ways.

In addition, YouTube has started to filter its content in an effort to block offensive videos from being made available. It’s not that the company gives a damn about what you view since there is already a plethora of super low quality videos over there, but it wants to avoid lawsuits. So, in a desperate effort to save its ass, YouTube has aggressively started filtering its content through any means necessary. This includes having its own unpaid workers, some dedicated users that have nothing else to do with their time, to do this deed for YouTube. Of course these people are not trained while the guidelines they have been given are vague at best. So, it’s up to their limited discernment to figure out what constitutes a bad video and what doesn’t, so what they flag is oftentimes seemingly random. This way, many legitimate videos have been filtered as inappropriate just because some idiot couldn’t tell what they were about. This resulted to the corresponding producer not receiving any revenue from these videos, despite the amount of work he/she has put into these projects.

Moreover, the revenue YouTubers make from a single video is not that high, unless the video goes viral. What’s worse, the revenue decreases exponentially since just the most recent and most popular videos attract enough viewership. Who cares about something that was published a year ago, right? Well, wrong. If a video is of a certain quality standard, it is bound to be good to watch even after a year or two after its release date. Then again, most YouTubers have given up on quality videos since those take a lot of time and they need to get something online soon, if it is going to be fresh. So, since I don't have a whole crew working for me, if I were to do YouTube videos I'd make a fairly small income from the videos themselves, unless of course I were to have some sponsor. Sponsor ads however are not something the viewer wants to watch, so once you have a sponsor in a video, its quality immediately drops.

Furthermore, as I have a better alternative to YouTube (the Safari platform), it makes no sense whatsoever to settle for a less professional platform. Besides, YouTube is only popular because it's been around the longest and with newer and better platforms entering the scene lately, it's doubtful this trend will continue. As a bonus for not working for YouTube, I don’t have to worry about the Article 13 issue that seems to trouble YouTubers, nor do I have to busk for subscriptions from my viewers. I still get some nasty comments from time to time, but the majority of the feedback I receive is positive.

Finally, there is also the recent fiasco with the YouTube Rewind 2018 video (which broke the record for the number of dislikes in a single video, as well as the record of how quickly a video accumulates dislikes). This may seem insignificant to the YouTube fanatic, whose allegiance to YouTube and Alphabet trumps any rational thoughts on this matter, but the fact is that the company doesn't care about its content creators. Otherwise, it would mention the ones that actually make a contribution to it, instead of veering away from them, in favor of a celebrity and some not so relevant YouTubers. I don't know about you, but I'd rather not make videos at all than publish my videos to a platform like this, which fails to appreciate its contributors.

So, if you are someone thinking of becoming a content creator and make a revenue from all this, there are better ways than YouTube. Perhaps it was a viable option once but right now it’s one of the worst places to publish your stuff. Besides, with Safari and other quality-based platforms out there, figuring out what to do with a quality video is really a  no-brainer.

(Image by lazyprogrammer.me)

PCA has attracted a lot of questions among all of my mentees over the years, so I decided to make a fairly in-depth video on the topic. Unlike other education material on PCA, this one is light on the math, while there is a lot of emphasis on the concepts as well as how they apply to a data scientist's work. You can check out the video on Safari here.

Note that in order to view the video in its entirety you'll need a subscription to the Safari platform. Cheers!

About 2 years ago I created a video on the Julia language and how it applies to data science. Although I was still learning the ropes of video creation, I had a lot of useful things to say about the language since I had just published a book on it, a book that is still quite popular among the Julia learners as well as those getting into data science through programming. Now, after version 1.0 has come out, I decided to revisit this topic and provide an update about how Julia factors in the whole data science matter, as well as how it contributes to A.I. applications among other relevant topics. In this video, I explore all these points and without getting too technical, I showcase an updated view of how Julia is still a relevant tool when it comes to data science projects. Enjoy!

Note that you'll need a subscription in order to be able to view this video on the Safari platform. However, once you have paid for it (either for a month or a year), you'll have access to all the content published in there, including all my other videos and books. Cheers!

As you may have heard, article 13 of the European copyright legislation is seen as a major issue for content creators of all sorts, sharing their creations online. Specifically, it can basically block the viewing of various videos (and other creative content) in various EU countries (including the UK). This is because this articles for some reason sees the viewing of this content in certain countries a violation of the content creators’ rights and in an effort to protect creativity, it limits where this content is made available.

I’m not going to argue here about the futility of such a legislation or why such laws don’t make any sense in a world where content creators strive for increased exposure, while it’s extremely unlikely for someone to own all the elements of their videos. Also, personal branding is something the lawyers that drafted this legislation probably don’t quite understand, something reflected in how this law is formulated. Whatever the case, this law is focused on various social media platforms, such as YouTube and Instagram and does not affect SafariBooksOnline.

So, if you are like me and publish your content in respectable platforms where there is a quality control and no issue with European legislation, you are fine. I can’t say that I like this situation with some bizarre law prohibiting the viewing of videos in various countries, but I’m not going to lose sleep over it since this is but the tip of the iceberg of injustices these “free” video platforms offer. Besides, there are various platforms where someone can publish creative content, especially when it comes to educational topics, so opting for the easy way of YouTube is just not the most professional approach. After all, the focus on such a platform is on the quantity and on some ever-changing algorithm for promoting this content, something that doesn’t benefit the content creator to start with.

So, if you have some ideas for educational videos, Safari is a great place to publish them and doesn’t get any headaches from the European Parliament or any other authority that claims to understand how creative content works. As a bonus, you get to collect royalties from your videos, regardless of when they were published or if they are on some “hot” topic, while click-bait is not that common in the video titles. This respect towards the viewers of the videos is reciprocated through a handsome payment from their part, instead of having to put up with annoying ads and overcrowded web pages. So perhaps going with YouTube is not as glamorous as it may seem, with or without Article 13.

So, after attending this truly eye-opening conference in Amsterdam last month, I felt obliged to share at least some of the stuff (most relevant to data science) I got from it with other people, through a reliable content sharing platform. So, I wrote an article about this topic on beBee and then created a video which is now available on Safari.

Note that this is a bit high-level as a video, with emphasis on managerial and senior-level data science practices, rather than hands-on aspects of the craft. However, every data scientist can benefit from this knowledge, especially when dealing with sensitive data. Also, Safari content requires a subscription in order to be accessible to its full length.

Lately I worked on a new series of videos, this time on Optimization. This A.I. methodology is a very popular one these days, one that adds a lot of value to both data science and other processes where resources are handled. Specifically, I talk about:
* Optimization in general (including its key applications)
* Particle Swarm Optimization
* Genetic Algorithms
* Simulated Annealing
* Optimization ensembles
* some auxiliary material that supplements these topics

You can find this video series on Safari, along with my other A.I. videos. Cheers!

Interestingly, the video throughput on Safari has increased lately so we don't have to wait too long before a video gets approved and published. This little guy, for example, I just finished on Thursday and it's already online at the Safari platform. It's by no means an exhaustive survey of the ML field, which is much larger than many people think and it doesn't include A.I. methods only. This video is more of an overview of ML and how it relates to other aspects of Data Science, such as Statistics, A.I., and various applications. So, if you are new to Data Science or want to get a comprehensive overview of the topic to supplement your studies of the subject, feel free to check it out!

With all the plethora of material out there for data science education, it is easy to get overwhelmed and even confused about what to study and how much time, money, and effort to put into it. Enter evaluation of data science material, a concise strategy for tackling this issue. In this 24 minute video, I talk about the various aspects of data science material, criteria for evaluating it, the matter of resources required to delve into this material, and some useful things to have in mind in your data science education efforts. Whether you are a newcomer to the field or a more seasoned data scientist, you have something to learn about data science (I know I do!) and this video can hopefully aid you in that. You can find it on Safari.

Note that in order to be able to view this video in its entirety, you'll need a subscription for the Safari platform. Also, it's important to remember that this video can offer you a framework for evaluating the data science material; you'll still need to find that material though and put the effort to study it, in order to make the most of it. The video can only help you organize your efforts more efficiently. Enjoy!

So, recently I decided to make a couple of videos on niche topics, namely the Business Aspect of A.I. in Data Science and  Extreme Learning Machines (ELMs). These vids are now available on Safari (here and here). Enjoy!

Note that in order to view these vids in their entirety you'll need a subscription to the platform. The latter enables you to view other materials, including a large variety of technical books as well as all my other videos. Cheers!