Backpropagation Collection

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⚔️Fighting

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“simple neural network library in ANSI C”

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⚙️Steel

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

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“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”

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“Notes for Deep Learning Specialization Courses led by Andrew Ng.”

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🌊Water

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“Artificial Neural Network”

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🔮Psychic

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“A complete GPT language model (training and inference) in ~600 lines of pure C#, zero dependencies”

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

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

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⚡Thunder

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“Implementing multilayer neural networks through backpropagation using Java.”

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

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

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🌀Psychic

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“Heterogeneous automatic differentiation ("backpropagation") in Haskell”

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🔮Psychic

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“Build neural networks based only on Numpy”

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“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”

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🔥Fire

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“A simple machine learning framework written in Swift 🤖”

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“Data science teaching materials”

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“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.”

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“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”