#Backpropagation
Showing 39 of 39 repositories tagged #backpropagation, ranked by stars
Efficiently computes derivatives of NumPy code.
simple neural network library in ANSI C
Deep learning in Rust, with shape checked tensors and neural networks
Notes for Deep Learning Specialization Courses led by Andrew Ng.
Artificial Neural Network
A complete GPT language model (training and inference) in ~600 lines of pure C#, zero dependencies
Implementing multilayer neural networks through backpropagation using Java.
Heterogeneous automatic differentiation ("backpropagation") in Haskell
Build neural networks based only on Numpy
A complete neural network built entirely in x86 assembly language that learns to recognize handwritten digits from the MNIST dataset. No frameworks, no high-level languages - just pure assembly - ~5.3ร faster than NumPy
A simple machine learning framework written in Swift ๐ค
Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
A neural network library written from scratch in Rust along with a web-based application for building + training neural networks + visualizing their outputs
Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera
Mathematics paper recapitulating the calculus behind a neural network and its back propagation
Classifying the Blur and Clear Images
A tiny neural network ๐ง
Awesome deep learning crate
An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
This code is part of my post on Medium.
Single-layer transformer in HyperTalk for the classic Macintosh
Simple multilayer perceptron c++ implementation.
This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. ็ฅ็ป็ฝ็ปๆจกๅ็็่ฎบ่ฏๆไธๅบไบNumpy็ๅฎ็ฐใ
Visualizing how deep networks make decisions
Computer code collated for use with Artificial Intelligence Engines book by JV Stone
Deep Learning Specialization course offered by DeepLearning.AI on Coursera
simple machine learning demo
Zero-dependency neural network in a single C header. Copy nerve.h, compile, done. Adam ยท ReLU ยท Dropout ยท Xavier/He ยท Neuroevolution game AI (Snake ยท Pong ยท Flappy Bird). No build system. No dependencies. Runs on Linux, macOS, Windows, and bare-metal.
PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
Caltech Machine Learning course notes and homework. Implements from scratch algorithms like SVM, neural networks, backpropagation, perceptrons and other linear classifiers.
Build a Neural Network from scratch in C++ to deeply understand how it works, not just how to use it.
Back Propagation, Python
RusTorch is a production-grade deep learning framework re-imagined in Rust. It combines the usability you love from PyTorch with the performance, safety, and concurrency guarantees of Rust. Say goodbye to GIL locks, GC pauses, and runtime errors. Say hello to RusTorch.
The only dynamic and reconfigurable Artificial Neural networks library with back-propagation for arduino
Axon is a spiking, biologically-based neural model driven by predictive error-driven learning, for systems-level models of the brain
This library provides a set of functionalities for different type of deep learning (and ML) algorithms in C
A simple multi-layer feed-forward neural network with backpropagation built in Swift.
Complement the article 'Differential Machine Learning' (Huge & Savine, 2020), including mathematical proofs and important implementation details for production
From linear regression towards neural networks...