Description
This practical guide introduces machine learning through clear explanations, useful examples, and hands-on projects that take readers from foundational concepts to advanced techniques. It covers supervised and unsupervised learning with Scikit-Learn, then progresses to neural networks and deep learning with TensorFlow. Along the way, readers learn how to prepare data, select and evaluate models, improve performance, and apply machine learning effectively to real-world problems. Accessible yet technically thorough, the book bridges theory and practice for aspiring data scientists, engineers, and developers.
Available Editions
paperback
O'Reilly Media
Published Apr 9, 2017
574 pages
ISBN: 9781491962299
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Details
First Published
2017
Language
eng
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