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Chapter Metrics

Generated by: Book Metrics Python Program v0.08
Generated on: June 03, 2026 at 12:10 PM

This file contains chapter-by-chapter metrics for student-facing content.

Chapter Name Sections Diagrams Equations Words Links Quiz Refs
1 Foundations of Artificial Intelligence and Natural Language Processing 15 0 1 4,789 12 10 0
2 Search Technologies and Indexing Techniques 18 0 0 6,453 14 10 0
3 Semantic Search and Quality Metrics 21 0 0 7,895 13 10 0
4 Large Language Models and Tokenization 12 2 0 6,835 14 10 0
5 Embeddings and Vector Databases 23 5 0 6,380 16 10 0
6 Building Chatbots and Intent Recognition 14 6 0 7,109 13 10 0
7 Chatbot Frameworks and User Interfaces 24 8 0 6,385 11 10 0
8 User Feedback and Continuous Improvement 21 6 0 6,531 12 10 0
9 The Retrieval Augmented Generation Pattern 24 4 0 6,168 19 10 0
10 Knowledge Graphs and GraphRAG 21 4 0 6,835 13 10 0
11 NLP Pipelines and Text Processing 18 4 0 7,259 16 10 0
12 Database Queries and Parameter Extraction 30 2 3 7,600 13 10 0
13 Security, Privacy, and User Management 30 1 0 3,832 14 10 0
14 Evaluation, Optimization, and Career Development 39 1 3 5,136 14 10 0

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:'
  • Equations: LaTeX expressions using $ and $$ delimiters
  • Words: Word count across all markdown files in the chapter
  • Links: Markdown-formatted links [text](url)
  • Quiz: Number of quiz questions in the chapter's quiz.md (0 if none)
  • Refs: Number of references in the chapter's references.md (0 if none)