Deep learning with Python

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-- ev...

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Bibliographic Details
Main Author : Chollet François (Auteur)
Format : Book
Language : anglais
Title statement : Deep learning with Python / François Chollet
Edition : Second edition
Published : Shelter island : Manning , 2021
Online Access : Via Nantes Université network
Access granted by using Nantes Université network, using a computer on the campus, via WiFi Eduroam or to people with an account @univ-nantes.fr or @etu.univ-nantes.fr
Online Access note : Attention, l'accès à la ressource est limitée à 3 utilisations simultanées
Subjects :
Related Items : Additional physical form: Deep learning with Python
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303 |a Notice rédigée d'après la consultation, 2022-05-18 
304 |a Titre provenant de l'écran d'accueil 
307 |a La pagination de l'édition imprimée correspondante est de : 478 pages 
320 |a Index 
330 |a 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. 
337 |a Nécessite un logiciel capable de lire un fichier aux formats HTML ou EPUB 
359 2 |b 1. What is deep learning?  |b 2. The mathematical building blocks of neural networks  |b 3. Introduction to Keras and TensorFlow  |b 4. Getting started with neural networks: classification and regression  |b 5. Fundamentals of machine learning  |b 6. The universal workflow of machine learning  |b 7. Working with Keras: a deep dive  |b 8. Introduction to deep learning for computer vision  |b 9. Advanced deep learning for computer vision  |b 10. Deep learning for timeseries  |b 11. Deep learning for text  |b 12. Generative deep learning  |b 13. Best practices for the real world  |b 14. Conclusions 
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