This is a topic that I'm pretty confident hasn't been featured much anywhere in the pop data science literature. Although it is quite well-known in the research sphere, most non-PhDs (and some PhDs too!) may have never heard about it, or why it is useful in day-to-day data science work. So, if you are one of those people who are curious and interested in learning even the less popular topics of our field, feel free to check it out on Safari.
Note that although I made an effort to cover this subject from various angles, this is still an introduction video to its topics. Also, some experience in data science would be immensely useful, otherwise the video may appear a bit abstract. Whatever the case, I hope you find it useful and use it as a jumping board to new aspects of data science that you were not aware of. Cheers!
Blockchain has been making waves in the past 10 years or so, with many applications like BitCoin and other cryptocurrencies that have been developed on this platform. Yet, there is also alternative platforms like Hashgraph that promise to deliver the same services but in a more efficient manner. All these technologies are under the umbrella of Distributed Ledger Technologies and are particularly important in our era of pronounced cyber-security concerns.
Recently I’ve put together a video on this topic that’s now available on Safari. It’s more high level but it covers all the key aspects of the technologies, making it ideal for someone new to the topic. What’s more, I’ve written a short article comparing the two technologies, on the DSP blog. Feel free to check them both out. Enjoy!
A/B testing is a crucial methodology / application in the data science field. Although it mainly relies on Statistics, it has a remained quite relevant in this machine learning and AI oriented era of our field. It's no coincidence that in Thinkful that's one of the first things data science students learn, once they get comfortable with descriptive Stats and basic data manipulation. So, I decided to do a video on this topic to help those interested in learning about it get a good perspective of it and understand better its relationship with Hypothesis Testing. It is my hope that this video can be a good supplement to one's learning on the subject. Enjoy!
A few years back, at a period I was both inspired to experiment with different Complex Systems and had enough time on my hands, I created this interesting variant of John Conway's Game of Life. As the beings in this model evolved, I named it the Game of Evolving Life. I ran a bunch of simulations on it and analyzed the results, a project that took the form of a whole ebook, which I never got around to publishing. Whatever the case, I thought this project would make a good example for the Complex Systems subtopic of the previous video's topic, so I made a video on it. This new video is now online on Safari. Enjoy!
Note that this video covers the main highlights of the model, with a very brief introduction to what complex systems are. Also, I focused on the more visual aspect of the analysis I'd done, otherwise it would be a much longer video that wouldn't be as interesting to most people. Finally, this whole thing was more of a programming exercise, so if you are looking at Data Science related videos that go into more depth on the methods of the craft, perhaps other videos would be better for you.
Randomness, Uncertainty, Complex Systems, and Applications Video Now Online + Shout-out to a Viewer of This Blog
This past week I decided to do a vid on an experimental topic, involving different fields, an interdisciplinary topic if you will. I understand the risks of such a video, since randomness is not particularly easy as a subject, while complex systems are a bit niche as a field. However, I tried to bring about a more intuitive approach to all this and introduce a new feature for such videos: mini-quizzes so that you can test your understanding while you watch the video. Anyway, feel free to check out this introductory video to this topic by visiting the corresponding Safari page. Warning: some of the stuff covered in this video veers aways from conventional approaches to this topic. Also, the video is very light on the math aspect of the topic as otherwise it would be too long and it's already over 30 minutes in length...
Also, recently a viewer of this blog, S.M., contacted me with some suggestions on how to tackle certain typo-related issues he had found. Big thanks to S.M. for his contribution!
Bias-Variance Trade-Off for Data Science & Backing Up and Wiping Out Sensitive Data Videos Are Now Online
This past week I've had some time off work as my CEO was on vacation. As a result I did 2 videos, not just 1. Here they are:
The Bias-Variance Trade-Off: when you have a model that favors a certain class or a certain set of values, you have high bias, while you have a model whose predictions are all over the place, you have high variance. Could you find a compromise between the two? And how does all this relate to the model's fitness? This video includes a few examples too, for classification and regression problems, to cement the concepts introduced.
Backing Up and Wiping Out Sensitive Data: you probably have heard of this topic and perhaps even apply it to some extent, since taking care of sensitive data is a good cyber-security habit to have, plus it's not new either. However, there is much more to it than that, like which storage media are best for back-up, how you can handle sensitive data on your computer without leaving a trace, and what software is out there that helps make that happen.
It seems like yesterday when I came up with this encryption system, for which I even wrote on this blog about. I never expected to create a video on it, but what better way to share it with the world, at least its core aspects of it. As there is no reason why I'd consider my implementation of this idea the best possible, I leave the viewer to experiment on his/her own on that matter, after I explain each aspect of the method and showcase a couple of examples of it. Anyway, check out the video on Safari when you get the chance and let me know here what you think of it. Enjoy!
So, the NLP Fundamentals video I made recently is online as of today (you can find it on the Safari site). Note that since Natural Language Processing is a very broad subject, it is quite hard to do it justice in a single video. However, for someone needing a good introduction to it, this video should be fine. Enjoy!
Even though this topic may be a bit polarizing, especially among people who are new to data science, knowing more about it can be very useful, particularly if you value a sense of perspective more than a good grade in some data science crash course. The latter is bound to overemphasize either Stats or AI, depending on the instructor's knowledge and experience. However, some data science professionals, myself included, prefer a more balanced approach on the topic. This is the reason why I decided to make this video, which is now available on Safari for your viewing.
Note that this is by no means a complete tutorial on the topic, but it is a good overview of the various aspects of statistics related to data science, along with some programming resources in both Python and Julia, to get you started. Enjoy!
Recently I decided to spice things up a bit and experiment with a new, more fresh approach to videos. As a result, I played around with graphics more, in an effort to go for a more intuitive presentation of the topic I looked at, namely sampling (check out the video here). Not all videos that ensue are going to be like that, but I’m definitely going to look into more interesting ways of tackling the graphics part.
This kind of video production takes a lot of work though and as I haven’t done graphics design in years, I’m a bit rusty and such a project takes a considerable amount of time. At the same time, I need to keep promoting my stuff online and one of the strategies I’ve found quite effective is through articles on beBee. As a result, I won’t be posting articles on my blog that often. However, if someone is interested in contributing to it, I’d be happy to consider guest authors on Data Science, A.I., Cyber-security, Programming, and other relevant topics.
Zacharias Voulgaris, PhD
Passionate data scientist with a foxy flair when it comes to technology, technique, and tests.