/Machine-Learning-Notes

This repo contains Comprehensive notes covering various machine learning concepts, algorithms, and applications, providing a structured resource for both beginners and experienced practitioners to deepen their understanding and proficiency in the field.

Primary LanguageJupyter NotebookMIT LicenseMIT

Machine-Learning-Practical-Notes

Regression Algorithms

  1. Linear Regression
  2. Ridge, Lasso and Elastic Net
  3. Decision Tree Regressor
  4. Random Forest Regressor
  5. Support vector regressor

Classification Algorithms

  1. Logistic Regression
  2. Naive Bayes
  3. K-nearest neighbors
  4. Support vector machines
  5. Decision Tree
  6. Random forest