Subject
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Exercises
Bookmarks
Pen & Paper Exercises in Machine Learning
Michael Gutmann's (Edinburgh) collection of pen-and-paper exercises covering the mathematical foundations of machine learning — linear algebra, optimization, graphical models, density estimation, and classification. Designed to build mathematical fluency that coding-first courses skip, using derivation rather than implementation as the primary learning mode.
100 Numpy Exercises
Nicolas Rougier's 100 exercises for NumPy, ranging from beginner to expert, covering the array operations that make NumPy indispensable. One of the most effective ways to internalize NumPy's vectorization mindset.