Here’s a good collection of cheatsheets for anyone involved with Big Data and machine learning. Whether you are already well versed in the subject, or just starting, I’m sure you’ll find something useful.
And while we are on the subject of machine learning, check out this repository for examples in Python, theory and math explanations behind many algorithms involved.
“Every Programmer Should Know” is a collection of subjects and resources that every programmer should know. It is not specific to any technology stack, and it’s rich enough to offer something to programmer of any level or experience.
I came across this rather useful and practical tutorial on Huffman Coding in JPEG images. It looks at a very small and basic black-and-white image, and how the size of the data and overhead changes between different image formats, and then in more detail, how the Huffman Coding helps make that happen.
Unless you are dealing with compression, image formats, and binary trees on a daily basis, this tutorial is a good memory refresher of those college days.
Here is a rather extensive collection of 350+ data structure problems with solutions. The list varies from the usual searching and sorting of values in an array, to string manipulation, binary logic, matrices and graphs. No matter how high was your grade for all those Computer Science courses back in college, or how long have you been programming, I guarantee you’ll find a challenge or two in this list.
From a very brief couple of hours look at the list, my favorite ones seem to be around the chessboard problems, such as this chess knight problem for finding the shortest path to destination using a queue.
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