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Deep Learning with Python
2nd edition
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- Nombre de pages478
- FormatGrand Format
- PrésentationBroché
- Poids1.055 kg
- Dimensions19,0 cm × 23,5 cm × 3,0 cm
- ISBN978-1-61729-686-4
- EAN9781617296864
- Date de parution23/11/2021
- ÉditeurManning
Résumé
Recent 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.
Deep 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 illustrations, and clear examples.
You'll quickly pick up the skills you need to start developing deep-learning applications. What's Inside : - Deep learning from first principles ; - Image classification and image segmentation ; - Time series forecasting ; - Text classification and machine translation ; - Text generation, neural style transfer, and image generation. For readers with intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.
Deep 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 illustrations, and clear examples.
You'll quickly pick up the skills you need to start developing deep-learning applications. What's Inside : - Deep learning from first principles ; - Image classification and image segmentation ; - Time series forecasting ; - Text classification and machine translation ; - Text generation, neural style transfer, and image generation. For readers with intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.