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Book
Deep Learning with Python
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ISBN: 9781617294433 1617294438 9781638352044 1638352046 Year: 2017 Publisher: Shelter Island Manning Publications

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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 AI researcher François Chollet, 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.


Book
Economie, économistes
Authors: ---
ISBN: 2200921527 9782200921521 Year: 2006 Publisher: Paris: Armand Colin,

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Dissertation
De la pseudo-paralysie de Parrot
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Year: 1895 Publisher: Bordeaux : Imprimerie et Lithographie Gagnebin,

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Book
Deep Learning with TensorFlow and Keras : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models.
Authors: --- --- ---
ISBN: 1803245719 Year: 2022 Publisher: Birmingham : Packt Publishing, Limited,

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Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML.

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