GitHub topics: autograd-engine
2BAD/micrograd
A TypeScript implementation of an autograd engine for educational purposes.
Language: TypeScript - Size: 321 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 2 - Forks: 0
NavneetKanna/dlgrad
An autograd engine built for my understanding
Language: Python - Size: 1.24 MB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 0 - Forks: 0
deependujha/DeepTensor
DeepTensor: A minimal PyTorch-like deep learning library focused on custom autograd and efficient tensor operations.
Language: C++ - Size: 1.35 MB - Last synced at: about 1 month ago - Pushed at: 4 months ago - Stars: 3 - Forks: 0
Ali-Mhrez/micrograd
A minimal scalar-valued autograd engine and neural network library inspired by Andrej Karpathy's backpropagation lecture.
Language: Jupyter Notebook - Size: 44.9 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
shivendrra/axon
numpy written in python from scratch
Language: Python - Size: 1.46 MB - Last synced at: 11 days ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0
ChanLumerico/autoprop
Auto Propagation System for Complex Neural Networks of Luma Python library
Language: Python - Size: 37.1 KB - Last synced at: about 2 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0
eljanmahammadli/gradipy
A Lightweight Deep Neural Network Library only using NumPy that offers Pytorch-like API
Language: Python - Size: 3.42 MB - Last synced at: 16 days ago - Pushed at: 10 months ago - Stars: 4 - Forks: 0
soheil555/nimmicrograd
Nim implementation of micrograd autograd engine
Language: Nim - Size: 10.7 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 0
mikex86/scicore
A tiny deep learning library written in Java
Language: Java - Size: 15.5 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 2
EliaFantini/Noise2Noise-Lite-two-ligther-versions-of-the-famous-AI-denoiser-for-small-images Fork of KieranVaudaux/DeepLearning
Noise2Noise is an AI denoiser trained with noisy images only. We implemented a ligther version which trains faster on smaller pictures without losing performance and an even simpler one where every low-level component was implemented from scratch, including a reimplementation of autograd.
Language: Jupyter Notebook - Size: 10.6 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
