This repository contains implementations of various machine learning algorithms from scratch in python with basic python functions and numpy library. Each algorithm is implemented in a separate file .
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forests
- KMean
- Perceptron
- Naives Bayes(Gaussian)
A major part of the project was adopted directly from the learning material. The motive behind the project is to learn the implementation of Machine Learning algorithm from scratch in Python
To use any of the implemented algorithms, simply navigate to the corresponding file and follow the instructions provided. Each algorithm is accompanied by a sample dataset for testing and demonstration purposes.
Assembly AI : Machine Learning from scratch playlist{link: https://www.youtube.com/watch?v=ltXSoduiVwY&list=PLcWfeUsAys2k_xub3mHks85sBHZvg24Jd&index=4}
Coursera : Advanced Learning Algorithm{link: https://www.coursera.org/learn/advanced-learning-algorithms}