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- 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

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.

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

Download this book in **EPUB** and **PDF** formats

Access this title in our online reader with advanced features

Publication date :
Oct 6, 2022

Length
698 pages

Edition :
3rd Edition

Language :
English

ISBN-13 :
9781803232911

Category :

Concepts :

Preface

1. Neural Network Foundations with TF

2. Regression and Classification

3. Convolutional Neural Networks

4. Word Embeddings

5. Recurrent Neural Networks

6. Transformers

7. Unsupervised Learning

8. Autoencoders

9. Generative Models

10. Self-Supervised Learning

11. Reinforcement Learning

12. Probabilistic TensorFlow

13. An Introduction to AutoML

14. The Math Behind Deep Learning

15. Tensor Processing Unit

16. Other Useful Deep Learning Libraries

17. Graph Neural Networks

18. Machine Learning Best Practices

19. TensorFlow 2 Ecosystem

20. Advanced Convolutional Neural Networks

21. Other Books You May Enjoy

22. Index

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Carlo Estopia
Feb 18, 2024

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