Deep learning library in python from scratch

Unsupervised Deep Learning-based Pansharpening with Jointly-Enhanced Spectral and Spatial Fidelity

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

Implementation of feedforward-backpropagated Neural Network from Scratch

Neural Networks Fundamentals with Python – implementing neural networks from scratch

Let's build Neural Networks from scratch.

Learn to build neural networks from scratch, simply. No autograd, no deep learning libraries - just numpy.

XOR gate which predicts the output using Neural Network 🔥

Pure Python Simple Neural Network (SNN) library

PyTorch implementation of Neural Style Transfer

Code for my youtube video: Neural Network Crash Course, Ep 1

Implementing Neural Networks using Maths and Numpy only

Implementation of George Hotz's tinygrad.

Multilayer Neural Network from Scratch.

Open Source neural network framework/architecture

Neural Network from scratch without any machine learning libraries

PyTorch seq2seq implementation. Includes pretrained models for jokes<>punchlines and english<>french.

Basic feedforward neural network written from scratch in Python along with a manual explaining how to implement basic neural networks

A NumPy-based deep learning library for building neural networks. It features an automatic differentiation engine and supports training models like LSTM, CNN, and FNN.

A complete convolutional neural network implemented from scratch