Tricking Data Science
Subtle code tricks and gem resources for all things data, machine learning and deep learning.
A book with no commitment
It starts with my dislike of bookmarks. As a programmer, you often come across a neat little code trick on StackOverflow or blogs by some elite senior, and say, "Hey, I gotta save this." You bookmark the page, and a day later you forget the bookmark's name. A week later, you even forget that it existed in the first place.But in your mind, you always have that fuzzy reference knowledge that there is some really cool way of doing this one task, but you can't really put your finger on it. All programmers experience this, and we all have different ways of dealing (or not dealing) with it. Well, this book is my way of dealing with it.
Tricking Data Science is a collection of code tricks, titbits of advice and curated resources that I picked up during the two years I have been writing about data science on Medium. Until I got recommended to the Jupyter Book project, there was no right way for me to organize such a collection but now, here it goes.
Don't ever reinvent the wheel
There is only one loose requirement for a certain code trick to be added to this book: It should perform a task in a short and concise way that most people don't know about and thus, waste their time reinventing the wheel. Today's languages and packages have been in use for such a long time now that there is always the best and shortest way of doing something. It is just a matter of looking in the right place. I hope this book will be that right place for many.
Don't shy away...
This is an open-source book, not an exclusive property of mine. If you have a trick or a resource of your own, create a pull request and give me the great satisfaction of accepting my very first! With your permission, I will add the trick to the book using Snappify—the tool I used for those interactive code blocks and maybe share it on LinkedIn.About the author
Here goes the semi-formal introduction of ME in the third person 😁
Bex Tuychiev is an undergraduate student studying business analytics (or something close to it) in Uzbekistan. He writes articles on data science, machine learning and statistics for the Medium publication Towards Data Science. With over 120 articles written, he currently ranks as one of the Top 10 all time Medium writers in the topic of Artificial Intelligence among 180k writers. Oh, and he is also a Kaggle Master and DataCamp instructor.
You can reach him for a chat or a sponsored article on LinkedIn, where he posts the contents of this book daily. Make sure your connection request has a custom message, otherwise, he just ignores them (yes, that sounds arrogant, but he isn't - at least, he hopes) 😉
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