/Machine-Learning-from-Scratch

The goal is to understand machine learning algorithms in depth.

Primary LanguageJupyter Notebook

Machine-Learning-from-Scratch: Contents

Regression:

Linear Regression from scratch with a single attribute.

Bayesian:

Naive Bayes Classifier

Gaussian Naive Bayes Classifier

Dimensionality Reduction:

Linear Disciminant Analysis

Prinipal Component Analysis

Instance Based:

K-Means Algorithm

Clustering:

K-Nearest-Neighbors

Neural Networks:

Perceptron with Backpropagation