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O'Reilly Media. 3. Very Good. Very Good. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported

New. BRAND NEW, GIFT QUALITY! NOT OVERSTOCKS OR MARKED UP REMAINDERS! DIRECT FROM THE PUBLISHER!

Used - Good. Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started.
Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit… Read More

UsedVeryGood. signs of little wear on the cover.

UsedVeryGood. Minor shelf wear

UsedVeryGood. signs of little wear on the cover.

UsedLikeNew. Remainder mark

UsedLikeNew. Remainder mark

UsedLikeNew. Remainder mark

New. .

New. .

New. .

Paperback / softback. New. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

O'Reilly Media, 2022 3rd Edition.. Soft cover. New.

paperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book.

O'Reilly Media. New. Special order direct from the distributor

Oreilly & Associates Inc, 2022. Paperback. New. 3rd edition. 850 pages. 9.19x7.00x1.71 inches.