Machine Learning Algorithms Implementation

This is a collection of machine learning algorithms implemented in python. Purpose: learning and practice.

Supervised Learning

• Linear Regression (Gradient Descent)
• Logistic Regression (Gradient Descent)
• Desicion Tree and Random Forest
• Adaboosting
• Naive Bayes
• K-nearest Neighbors

Unsupervised Learning

• K-means Clustering
• Non-negative matrix factorization
• Recommendation System
  • Collaborative Filtering
  • Matrix Factorization

Testing

• Multi-Armed Bandit problem