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

Implementations of deep learning optimizers using NumPy. Featuring SGD, Adam, Adagrad, NAG, RMSProp, and Momentum. This repo also includes a benchmark against Pytorch developed optims.

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

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.

Implementation of artificial neural networks

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.

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

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

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

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 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)

OmniNumPy is an experimental compatibility layer that sits on top of modern NumPy (≥2.0) and lets you run the same code across multiple array backends — NumPy, PyTorch, CuPy, and JAX — with minimal changes.

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

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

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

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