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.

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 :-)

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

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

Trained deep neural networks to predict and classify input image (MNISTDD) datasets with python.

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 :-)

Dimag, Nepali for the brain is an object-oriented neural network framework developed by me using python3.