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Machine Learning Algorithms in Depth dives deep into the 'how' and the 'why' of machine learning algorithms. For each category of an algorithm, you will go from math-first principles to hands-on implementation in Python. You will explore dozens of examples from across all the fields of machine learning, including finance, computer vision, NLP, and more. Each example is accompanied by worked-out derivations and details as well as insightful code samples and graphics. By the time you're done reading, you will know how major algorithms work under the hood -- and be a better machine learning practitioner.
About the reader For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus.