Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.
This repository holds one of my first Deep Learning projects. The project implements an MNIST classifying fully-connected neural network from scratch (in python) using only NumPy for numeric computations. For further information, please see README.
This project deals with implementation of various machine learning models from scratch in python( jupyter notebook) without actually importing them from the sklearn library.
Machine Learning from Scratch. From Scratch implementation of famous machine learning techniques using Numpy. Focus on readiness with step by step documentation.
Machine Learning From Scratch. Bare bones implementations of machine learning models and algorithms. Aims to cover everything from linear regression to deep learning.