Contents

1. Cover
2. Front Matter
3. 1. Introduction
4. 2. Introduction to Machine Learning
5. 3. Deep Learning and Neural Networks Overview
6. 4. Complementary Libraries to TensorFlow 2.x
7. 5. A Guide to TensorFlow 2.0 and Deep Learning Pipeline
8. 6. Feedforward Neural Networks
9. 7. Convolutional Neural Networks
10. 8. Recurrent Neural Networks
11. 9. Natural Language Processing
12. 10. Recommender Systems
13. 11. Autoencoders
14. 12. Generative Adversarial Network
15. Back Matter

Landmarks

1. Cover
2. Table of Contents
3. Body Matter