Chapter Metrics
This file contains chapter-by-chapter metrics.
| Chapter | Name | Sections | Diagrams | Words |
|---|---|---|---|---|
| 1 | Foundations of Artificial Intelligence and Natural Language Processing | 15 | 0 | 4,790 |
| 2 | Search Technologies and Indexing Techniques | 18 | 0 | 6,453 |
| 3 | Semantic Search and Quality Metrics | 21 | 0 | 7,895 |
| 4 | Large Language Models and Tokenization | 12 | 2 | 6,835 |
| 5 | Embeddings and Vector Databases | 23 | 5 | 6,380 |
| 6 | Building Chatbots and Intent Recognition | 14 | 6 | 7,109 |
| 7 | Chatbot Frameworks and User Interfaces | 24 | 8 | 6,385 |
| 8 | User Feedback and Continuous Improvement | 21 | 6 | 6,531 |
| 9 | The Retrieval Augmented Generation Pattern | 24 | 4 | 6,168 |
| 10 | Knowledge Graphs and GraphRAG | 21 | 4 | 6,835 |
| 11 | NLP Pipelines and Text Processing | 18 | 4 | 7,259 |
| 12 | Database Queries and Parameter Extraction | 30 | 2 | 7,600 |
| 13 | Security, Privacy, and User Management | 30 | 1 | 3,832 |
| 14 | Evaluation, Optimization, and Career Development | 39 | 1 | 5,136 |
Metrics Explanation
- Chapter: Chapter number (leading zeros removed)
- Name: Chapter title from index.md
- Sections: Count of H2 and H3 headers in chapter markdown files
- Diagrams: Count of H4 headers starting with '#### Diagram:'
- Words: Word count across all markdown files in the chapter