Machine Learning for everyone

This repository's first purpose was to mantain a track of all algorithms I've been implementing during a year or so of doing research projects. But as of writing these algorithms I realized that putting all this code to the public could help somebody out there to understand the basic Machine Learning algorithms, so use it as you want, but would be cool if you star or reference this repository!

Prerequisites

• Python 3.8+
• Pipenv
• Basic machine learning knowledge
• Basic numpy and pytorch knowledge

Installation

$ git clone https://github.com/helloerikaaa/ML-for-everyone.git
$ cd Ml-for-everyone
$ pipenv shell
$ pipenv install

List of implementations

Basic

• Perceptron

Supervised Learning

• Naive Bayes
• Linear Regression
• Polynomial Regression

Unsupervised Learning

• K-Means

Reinforcement Learning

• Deep Q Network

Convolutional Neural Network Models

• VGG16
• AlexNet
• GoogleNet

Activation Functions

• Sigmoid
• ReLU
• Softmax

Loss Functions

• Square Loss
• Cross Entropy

Optimizers

• Adam
• AdaGrad
• Adadelta

Reference

[1] Sánchez-Femat, Erika P. (2021) Machine Learning for everyone [Source Code]
https://github.com/helloerikaaa/ML-for-everyone