(COLORED) Deep Learning with Python, 2nd Edition, Francois Chollet

Printed in full color! Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world. \n \nIn Deep Learning with Python, Second Edition you will learn: \n \nDeep learning from first principles \nImage classification and image segmentation \nTimeseries forecasting \nText classification and machine translation \nText generation, neural style transfer, and image generation \nFull color printing throughout \n \nDeep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised full color second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. You’ll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks. \n \nPurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. \n \nAbout the technology \nRecent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach—even if you have no background in mathematics or data science. This book shows you how to get started. \n \nAbout the book \nDeep Learning with Python, Second Edition introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations, crisp color illustrations, and clear examples. You’ll quickly pick up the skills you need to start developing deep-learning applications.

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