Machine Learning Examples
Simple from-scratch implementations of foundational machine learning algorithms for study and reference.
Project Overview
A reference collection of foundational machine learning algorithms, implemented and documented in Jupyter notebooks while studying the underlying math behind common ML techniques.
Implemented Algorithms
- K-Nearest Neighbors (KNN): Classification based on the closest labeled examples in feature space.
- Linear Regression: Fitting a linear model to continuous data.
- Perceptron: The simplest binary linear classifier and building block of neural networks.