Python Book 7 - Python for Deep Learning for Novices/ Keras and PyTorch

Table of Contents

1. Introduction

1.1 What is Deep Learning?

1.2 Why Python for Deep Learning?

1.3 What are Keras and PyTorch?

1.4 How to Install and Use Keras and PyTorch?

1.5 A Simple Example of Deep Learning with Keras and PyTorch 2. Basic Concepts of Deep Learning

2.1 Neural Networks

2.2 Activation Functions

2.3 Loss Functions

2.4 Optimization Algorithms

2.5 Regularization Techniques

2.6 Evaluation Metrics

3. Common Deep Learning Models

3.1 Feedforward Neural Networks

3.2 Convolutional Neural Networks

3.3 Recurrent Neural Networks

3.4 Autoencoders

3.5 Generative Adversarial Networks

4. Deep Learning Applications

4.1 Image Classification

4.2 Object Detection

4.3 Natural Language Processing

4.4 Speech Recognition

4.5 Recommender Systems

5. Advanced Topics of Deep Learning

5.1 Transfer Learning

5.2 Attention Mechanism

5.3 Transformer Models

5.4 Reinforcement Learning

5.5 Explainable AI

6. Conclusion

6.1 Summary of the Book

6.2 Future Trends of Deep Learning 6.3 Resources for Further Learning