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[eBook] [PDF] Machine Learning Fundamentals A Concise Introduction, 1st Edition By Hui Jiang

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This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear a... lgebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. Succinct rather than exhaustive, the focused presentation and coherent overview framework allows readers to understand the core ideas and learn implementations quickly Over 200 color illustrations and more than 50 worked examples, case studies, lab projects in MATLAB and Python, and numerous exercises aid understanding Covers recent important developments in AI and deep learning as well as traditional supervised machine learning methods [Show More]

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