# Machine learning basics

This repository contains implementations of basic machine learning algorithms in plain Python (Python Version 3.6+). All algorithms are implemented from scratch without using additional machine learning libraries. The intention of these notebooks is to provide a basic understanding of the algorithms and their underlying structure, *not* to provide the most efficient implementations.

- Linear Regression
- Logistic Regression
- Perceptron
- k-nearest-neighbor
- k-Means clustering
- Simple neural network with one hidden layer
- Multinomial Logistic Regression
- Decision tree for classification
- Decision tree for regression

## License

See the LICENSE file for license rights and limitations (MIT).