Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.

Implementation of Adam Optimization algorithm using Numpy

deep learning from scratch. uses numpy/cupy, trains in GPU, follows pytorch API

Nice place to start seeing matrices shapes ! Great place for beginners to understand neural networks computation

Implementation of artificial neural networks

Python3 implementation of the Unsupervised Deep Learning Algorithm, Restricted Boltzmann Machine.

A simple fully connected feed forward neural network written in python from scratch using numpy & optimized using numba. It is possible to have multiple hidden layers, change amount of neurons per layer & have a different activation function per layer.

Computer vision project that utilized openCV to detect a soccer ball and players in a livestream of a soccer game.

NumPy (short for Numerical Python) is a powerful Python library used for working with arrays, matrices, and numerical computations.

A proof of concept of a recursion doing stochastic gradient descent for a simple neural network. Done in Python3 with numpy

Small NeuralNet-Framework implemented with NumPy (Convolution|TransposeConv|Linear)

I made fully connected neural network in plain NumPy to classify digits from the MNIST dataset! It achieves 95% accuracy :-)

Classifies different types of wheat seeds by Artificial Neural Network using Numpy.

Assignment codes, and general work for pes io course Neural Networks Unleashed

This repository contains an implementation of a neural network from scratch using only NumPy, a fundamental library for numerical computing in Python. The neural network is designed to perform tasks such as classification, regression, or any other supervised learning problem.

TCC do curso de Análise e Desenvolvimento de Sistemas - FATEC - A Utilização de Algoritmos Genéticos na Otimização de Problemas

I made LeNet5 (one of the first convolution neural networks) in plain NumPy to classify digits from the MNIST dataset! Accuracy reaches 91.5% after one epoch :-)

A simple homebrew neural network created for MTE 203.

Fundamental Machine Learning Algorithms implemented from scratch. This is an on going repository and will be updated in future.