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![Machine Learning Algorithms in Depth (MEAP v7)](/uploads/posts/2023-03/1679068965_4081_machin__l_arning_algorithms_in_d_pth__m_ap_v07_.jpg)
Автор: Vadim Smolyakov
Издательство: Manning Publications
Год: 2023
Страниц: 267
Язык: английский
Формат: pdf (true)
Размер: 46.1 MB
Develop a mathematical intuition for how Machine Learning (ML) algorithms work so you can improve model performance and effectively troubleshoot complex ML problems. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting Machine Learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you’ll learn the fundamentals of Bayesian inference and Deep Learning. You’ll also explore the core data structures and algorithmic paradigms for Machine Learning. Each algorithm is fully explored with both math and practical implementations so you can see how they work and how they’re put into action. For each category of algorithm, you’ll go from math-first principles to a hands-on implementation in Python, exploring dozens of examples from across all the fields of machine learning. Each example is accompanied by worked-out derivations and details, as well as insightful code samples and graphics.