Linear Regression Model from Scratch

This project goal was to explain and implement a simple Linear Regression model.
For that, a class with methods of fit and predict was build.
For this implementation, it was only used numpy and python, since the main purpose was to develop the mathematical basis of the model.
In order to test the model, synthetic data was created with sklearn make_regression method.
Check out in Github ↓

Github Repository

K Nearest Neighbors Model from Scratch

This project goal was to explain and implement a simple K Nearest Neighbors classifier model.
For that, a class with methods of fit and predict was build.
For this implementation, it was only used numpy and python, since the main purpose was to develop the mathematical basis of the model.
In order to test the model, a famous pre loaded model from sklearn was uses (iris model)
Check out in Github ↓

Github Repository

K Means Clusterization Model from Scratch

This project goal was to explain and implement a simple K Means CLusterization model.
For that, a class with method predict was build.
For this implementation, it was only used numpy and python, since the main purpose was to develop the mathematical basis of the model.
In order to test the model, a sklearn sinthetic dataset builder was used.
Check out in Github ↓

Github Repository