Deep Learning with TensorFlow and Keras Build and deploy supervised, unsupervised, deep, and reinforcement learning models

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  • Engels
  • Paperback
  • 9781803232911
  • 04 november 2022
  • 698 pagina's
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Samenvatting

Deep Learning with TensorFlow and Keras, Third Edition teaches deep learning techniques alongside TensorFlow (TF) and Keras. The book introduces neural networks with TensorFlow, runs through the main applications, covers two working example apps, and then dives into TF and cloud in production, TF mobile, and using TensorFlow with AutoML.



Build cutting edge machine and deep learning systems for the lab, production, and mobile devices.

Purchase of the print or Kindle book includes a free eBook in PDF format.

Key Features
  • Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples
  • Implement graph neural networks, transformers using Hugging Face and TensorFlow Hub, and joint and contrastive learning
  • Learn cutting-edge machine and deep learning techniques
Book Description

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.

What you will learn
  • Learn how to use the popular GNNs with TensorFlow to carry out graph mining tasks
  • Discover the world of transformers, from pretraining to fine-tuning to evaluating them
  • Apply self-supervised learning to natural language processing, computer vision, and audio signal processing
  • Combine probabilistic and deep learning models using TensorFlow Probability
  • Train your models on the cloud and put TF to work in real environments
  • Build machine learning and deep learning systems with TensorFlow 2.x and the Keras API
Who this book is for

This hands-on machine learning book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow, and AutoML to build machine learning systems.

Some machine learning knowledge would be useful. We don't assume TF knowledge.

Productspecificaties

Inhoud

Taal
en
Bindwijze
Paperback
Oorspronkelijke releasedatum
04 november 2022
Aantal pagina's
698

Betrokkenen

Hoofdauteur
Amita Kapoor
Tweede Auteur
Antonio Gullì
Hoofduitgeverij
Packt Publishing Limited

Overige kenmerken

Editie
3
Product breedte
75 mm
Product lengte
93 mm
Studieboek
Ja
Verpakking breedte
75 mm
Verpakking hoogte
93 mm
Verpakking lengte
93 mm
Verpakkingsgewicht
1280 g

EAN

EAN
9781803232911

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