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!

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.

Enjoy!

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.

Happy π day everyone! π (usually pronounced as "pie") is a very important constant in Mathematics and although it's not so relevant to this blog, I decided to celebrate it through this video. What does a passwords vid have to do with π? Well, it's not just about Passwords, since it also covers Information, and Entropy. This is why it was code named PIE during its production last week. To be honest, I wasn't expecting that it would be published on the actual π day, but stranger things have happened!

Anyway,  if you want to learn more about this fascinating topic through a fairly lightweight video full of useful tips on how to evaluate passwords and how to create strong yet memorable ones, this is the video for you. Check it out on Safari when you have a moment!

After investigating this topic quite a bit, as I was looking into A.I. stuff, I decided to create a video on it. To make it more complete, I included other methods too, such as Statistics-based and heuristics-based ones. Despite the excessive amount of content I put together into this project (the script was over 4000 words), I managed to keep the video at a manageable length (a bit less than half an hour). Check it out on Safari when you have some time!
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Although it's been over 2 weeks since I finished working on the Data Visualization video and about a month since I completed the Deep Learning one, both of them just got made available on Safari (a subscription based platform for various educational material). So, if you are up for some food for thought on DL and DV, check them out when you have a moment: Deep Learning vid and Data Visualization vid.

Note that these are both overview videos and although in the Data Viz one I include several references to libraries in Python and Julia for creating various plots, the videos are fairly high-level. These are not in-depth tutorials on the topics.

Once I decide to take a break from all the book-writing these days, I'll probably make another video either on AI or on a more conventional DS topic. So, stay tuned...

For the past few months I've been working on a tutorial on the data modeling part of the data science process. Recently I've finished it and as of 2 weeks ago, it available online at the Safari portal. Although this tutorial is mainly for newcomers to the field, everyone can benefit from it, particularly people who are interested in not just the technical aspects but also on the concepts behind them and how it all relates to the other parts of the pipeline. Enjoy!