backpropagation

Efficiently computes derivatives of NumPy code.

simple neural network library in C99

Deep learning in Rust, with shape checked tensors and neural networks

数学知识点滴积累 矩阵 数值优化 神经网络反向传播 图优化 概率论 随机过程 卡尔曼滤波 粒子滤波 数学函数拟合

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

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

Six snippets of code that made deep learning what it is today.

Implementing multilayer neural networks through backpropagation using Java.

A collection of all projects pertaining to different layers in the SDC software stack

Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz

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 - ~5.3× faster than NumPy

This Repository contains Solutions to the Quizes & Lab Assignments of the Mathematics for Machine Learning Specialization offered by Imperial College of London on Coursera taught by David Dye, Samuel J. Cooper, A. Freddie Page, Marc Peter Deisenroth

A simple machine learning framework written in Swift 🤖

Data science teaching materials

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