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Chapter Metrics

This file contains chapter-by-chapter metrics.

Chapter Name Sections Diagrams Words
1 Introduction to Machine Learning Fundamentals 23 0 4,244
2 K-Nearest Neighbors Algorithm 17 0 3,533
3 Decision Trees and Tree-Based Learning 19 0 3,602
4 Logistic Regression and Classification 29 0 4,143
5 Regularization Techniques 32 0 3,702
6 Support Vector Machines 36 0 4,558
7 K-Means Clustering and Unsupervised Learning 41 0 4,794
8 Data Preprocessing and Feature Engineering 43 0 4,361
9 Neural Networks Fundamentals 59 0 5,055
10 Convolutional Neural Networks for Computer Vision 39 0 4,561
11 Transfer Learning and Pre-Trained Models 21 0 5,487
12 Model Evaluation, Optimization, and Advanced Topics 32 0 6,160

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