This repository contains Python implementation of ML algorithms, built either from scratch or by using sk-learn library.
- Feature Engineering
- Linear Regression with L2 regularization
- Linear Regression with SGD (Stochastic Gradient Descent)
- Kernel Linear Regression
- Logistic Regression with SGD
- Grid Search
- Gradient Boosting Trees
- Decision Tree
- Random Forest
- Bootstrap Resampling
- Naive Bayes
- Support Vector Machines (SVM)
- Sequential minimal optimization (SMO)
- Gaussian Mixture
- K-means
- KNN (K Nearest Neighbors)
- Principal component analysis (PCA)
- Softmax Classification with SGD
- Multi-layer perceptron (MLP) classification with SGD
- Perceptron