Development

Start: 10/2022.

End: 06/2023.

Project description (Link to guide)

I made a machine learning guide that includes all stages of its development, main techniques and algorithms developed to date, as well as websites, codes and auxiliary tutorials. It has more than 300 pages, and can help you discover new tools and algorithms that you may never heard of before.

Chapters Include:

  • Ethics
  • Concepts
  • Pre-Processing
  • Feature Selection
  • Regression
  • Classification
  • Clusters
  • Recommendation
  • Time-Series
  • Neural Networks
  • Reinforcement Learning
  • Ensemble Methods
  • Explainable Models (XAI)
  • AutoML
  • Cost-Sensitive Learning
  • Dimension Reduction
  • Anomaly Detection
  • Model Tuning
  • Evaluation metrics
  • Statistics
  • Model Compression
  • Python and R tools
  • Storytelling with Data
  • AI tools
  • Tutorials, Courses, Code Examples, Books
  • And more…