Deep Learning with Python

Par : François Chollet

Formats :

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  • Nombre de pages361
  • PrésentationBroché
  • FormatGrand Format
  • Poids0.711 kg
  • Dimensions18,7 cm × 23,6 cm × 2,7 cm
  • ISBN978-1-61729-443-3
  • EAN9781617294433
  • Date de parution28/10/2017
  • ÉditeurManning

Résumé

Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google Al researcher François Challes, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models.
By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google Al researcher François Challes, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models.
By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.