DL Book 7 - Transfer Learning with Pre-Trained Models for Novices

Table of Contents

1. Introduction

1.1 What is Transfer Learning?

1.2 Why Use Transfer Learning?

1.3 Types of Transfer Learning

1.4 Challenges and Limitations of Transfer Learning

2. Pre-Trained Models

2.1 What are Pre-Trained Models?

2.2 How to Choose a Pre-Trained Model?

2.3 Popular Pre-Trained Models for Different Tasks and Domains 2.4 How to Access and Use Pre-Trained Models?

3. Transfer Learning Techniques

3.1 Feature Extraction

3.2 Fine-Tuning

3.3 Domain Adaptation

3.4 Multi-Task Learning

3.5 Meta-Learning

4. Transfer Learning Applications

4.1 Transfer Learning for Computer Vision

4.2 Transfer Learning for Natural Language Processing

4.3 Transfer Learning for Speech Recognition

4.4 Transfer Learning for Recommender Systems

4.5 Transfer Learning for Reinforcement Learning

5. Transfer Learning Best Practices

5.1 Data Preparation and Augmentation

5.2 Model Selection and Evaluation

5.3 Hyperparameter Tuning and Optimization

5.4 Transfer Learning Ethics and Fairness

6. Conclusion

6.1 Summary of Key Points

6.2 Future Trends and Directions