Linear Algebraic Tools in Machine Learning and Data Science
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About the book:
Math and Architectures of Deep Learning sets out the foundations of DL in a way thatโs both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. Youโll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research.