Math for Deep Learning: A Practitioner's Guide to Mastering Neural Networks by Ronald T. Kneusel

Math for Deep Learning: A Practitioner's Guide to Mastering Neural Networks

Ronald T. Kneusel

344 pages first pub 2021 (editions)

challenging informative medium-paced
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You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gr...

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