Book Content
chapters • 10h52m total length
1. Natural Language Understanding, Related Technologies, and Natural Language Applications
2. Identifying Practical Natural Language Understanding Problems
3. Approaches to Natural Language Understanding – Rule-Based Systems, Machine Learning, and Deep Learning
4. Selecting Libraries and Tools for Natural Language Understanding
5. Natural Language Data – Finding and Preparing Data
6. Exploring and Visualizing Data
7. Selecting Approaches and Representing Data
8. Rule-Based Techniques
9. Machine Learning Part 1 - Statistical Machine Learning
10. Machine Learning Part 2 – Neural Networks and Deep Learning Techniques
11. Machine Learning Part 3 – Transformers and Large Language Models
12. Applying Unsupervised Learning Approaches
13. How Well Does It Work? – Evaluation
14. What to Do If the System Isn’t Working
15. Summary and Looking to the Future
