Machine-Learning-Algorithms-from-Scratch

This repo aims to dive deeper into machine learning by implementing machine learning algorithms from scratch. The folder structure is as follows. Every algotithm have implementation file .py and also simple tests as jupyter notebooks.

• Classification
  • Logistic Regression
  • Support Vector Machine
  • Decision Tree
  • Random Forest
• Regression
  • Linear Regression
  • Decision Tree
  • Random Forest
  • Gradient Boost
  • XGBoost
• Unsupervised Algorithms
  • Principal Component Analysis