AI & ML · Ebook

TensorFlow and Keras: Practical Deep Learning

by Shriira Press

A comprehensive, self-contained guide to TensorFlow and Keras, the framework with which much of the world builds and ships deep-learning models. Where the companion Scikit-Learn book covers classical machine learning, this book picks up exactly where scikit-learn deliberately stops: neural networks — the deep models behind modern computer vision, language, audio, and generative AI. It teaches the practical craft — tensors and automatic differentiation, the three Keras model-building APIs, training loops, tf.data input pipelines, CNNs and sequence models, transfer learning, and the full road to deployment on servers, mobile, and the web. It blends intuition, the concepts behind the API, and runnable code.

Contents

1. 1Preface
2. 2Chapter 1 — What Is TensorFlow and Keras?
3. 3Chapter 2 — Tensors and the TensorFlow Core
4. 4Chapter 3 — Your First Neural Network with Keras
5. 5Chapter 4 — The Keras APIs: Sequential, Functional, and Subclassing
6. 6Chapter 5 — Layers, Activations, and Building Blocks
7. 7Chapter 6 — Training: Losses, Optimizers, Metrics, and Loops
8. 8Chapter 7 — Data Pipelines with tf.data
9. 9Chapter 8 — Convolutional Networks for Images
10. 10Chapter 9 — Sequence Models: RNNs, LSTMs, and Attention
11. 11Chapter 10 — Regularization, Tuning, and Avoiding Overfitting
12. 12Chapter 11 — Transfer Learning and Pretrained Models
13. 13Chapter 12 — Saving, Serving, and Deployment
14. 14Chapter 13 — The Ecosystem, Scaling, and the Profession
15. 15Appendix A — Glossary and API Quick Reference
16. 16Appendix B — Further Reading and Resources