10 Best Books On Machine Learning

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BOOK: "Machine Learning: 4 Books in 1" A comprehensive guide for beginners covering Python programming and artificial intelligence through data science

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BOOK: "Mathematics for Machine Learning" A tool to understand the mathematical foundations of machine learning, covering topics like linear algebra, probability, optimization, and statistics

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BOOK: "Linear Algebra and Optimization for Machine Learning" Provides a comprehensive introduction to linear algebra and optimization, essential topics in machine learning

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BOOK: "The Hundred-Page Machine Learning Book" by Andriy Burkov Offers a concise yet comprehensive overview of machine learning concepts for beginners

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BOOK: "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron

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BOOK: "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

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BOOK: "Data Science from Scratch" by Joel Grus A comprehensive introduction to fundamental tools and techniques of data science, suitable for beginners

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BOOK: "Machine Learning for Absolute Beginners" by Oliver Theobald

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BOOK: "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig

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BOOK: "Atlas of AI" by Kate Crawford Explores the history and societal impacts of AI and machine learning technologies, offering insights into their ethical implications

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BOOK: "Architects of Intelligence" by Martin Ford Features interviews with top AI researchers and industry leaders, providing insights into the future of AI

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FOR MORE OF SUCH RECOMMENDATIONS

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