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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

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Practical ML mastery from code to deployment

If you want a machine learning book that actually gets you building, this is the one people often rave about. It keeps theory approachable and ties everything to real Python workflows with Scikit-Learn, Keras, and TensorFlow, so the learning feels useful fast. It is especially great for programmers who want to move from curiosity to confidently training, tuning, and shipping intelligent systems.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
Just Arrived

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Regular price RM44.00 MYR
Unit price
per
Compare to estimated retail price: RM280.00 MYR  
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ISBN: 9781492032649
Authors: Aurélien Géron
Publisher: O'Reilly Media
Date of Publication: 2019-10-15
Format: Paperback
Related Collections: Science
Related Topics: Mathematics, Computers
Goodreads rating: 4.55
(rated by 2827 readers)

Description

Through a series of recent 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. The updated edition of this best-selling book uses concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow 2—to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. Practitioners will learn a range of techniques that they can quickly put to use on the job. Part 1 employs Scikit-Learn to introduce fundamental machine learning tasks, such as simple linear regression. Part 2, which has been significantly updated, employs Keras and TensorFlow 2 to guide the reader through more advanced machine learning methods using deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. NEW FOR THE SECOND EDITION: Updated all code to TensorFlow 2. Introduced the high-level Keras API. New and expanded coverage including TensorFlow's Data API, Eager Execution, Estimators API, deploying on Google Cloud ML, handling time series, embeddings and more. With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released.
 

Practical ML mastery from code to deployment

If you want a machine learning book that actually gets you building, this is the one people often rave about. It keeps theory approachable and ties everything to real Python workflows with Scikit-Learn, Keras, and TensorFlow, so the learning feels useful fast. It is especially great for programmers who want to move from curiosity to confidently training, tuning, and shipping intelligent systems.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.