1019 Open source projects that are alternatives of or similar to Cython Blis

Benchmark MATLAB & Julia for Matrix Operations

High level linear algebra library for Dlang

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

A blazing fast matrix library for Elixir/Erlang with C implementation using CBLAS.

A flexible framework of neural networks for deep learning

A #[no_std] LinAlg library

OCaml bindings for BLAS/LAPACK (high-performance linear algebra Fortran libraries)

A fast vector/matrix library

Grokking Deep Reinforcement Learning

Linear algebra in TypeScript.

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

BLAS extension to xtensor

Armadillo: fast C++ library for linear algebra & scientific computing - http://arma.sourceforge.net

SADDLE: Scala Data Library

Linnea is an experimental tool for the automatic generation of optimized code for linear algebra problems.

Fused Matrix Library

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

Pure Javascript manually written 👌 implementation of BLAS, Many numerical software applications use BLAS computations, including Armadillo, LAPACK, LINPACK, GNU Octave, Mathematica, MATLAB, NumPy, R, and Julia.

DBCSR: Distributed Block Compressed Sparse Row matrix library

monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

A compile-time linear algebra system for C++

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

An intelligent block matrix library for numpy, PyTorch, and beyond.

Basic linear algebra subroutines for embedded optimization

Scala Native BLAS (Basic Linear Algebra Subprograms) supporting Linux and macOS

BLAS-like Library Instantiation Software Framework

Modern Fortran Interfaces to BLAS and LAPACK

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

Kokkos C++ Performance Portability Programming EcoSystem: Math Kernels - Provides BLAS, Sparse BLAS and Graph Kernels

THIS MIRROR IS DEPRECATED -- New url: https://gitlab.com/libeigen/eigen

Numpy Audio DSP Tools

A single / multi layer / recurrent neural network written in Golang.

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

LiTS - Liver Tumor Segmentation Challenge

A Simple & Flexible Cross Framework Operators Toolkit

Code repository for Frontiers article 'Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT'

Performance analysis of predictive (alpha) stock factors

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.

Scalable Implementation of Deep CFR and Single Deep CFR

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)

Kalman Filter implementation in Python using Numpy only in 30 lines.

Avalanche: a End-to-End Library for Continual Learning.

Main repository for Mantid code

Labs for the Foundations of Applied Mathematics curriculum.

[NO MAINTENANCE INTENDED] A PyTorch implementation of CapsNet architecture in the NIPS 2017 paper "Dynamic Routing Between Capsules".

🛠 All-in-one web-based IDE specialized for machine learning and data science.

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!

📚 Various cheatsheets in PDF

image processing codes to understand algorithm

Probabilistic time series modeling in Python

Using word vectors to classify spam messages

Frame-Recurrent Video Super-Resolution (official repository)

Numerical linear algebra software package

Automated Testing for Set-Top Boxes and Smart TVs

Technical Analysis Library using Pandas and Numpy