Train AI models - not your patience

The Unified AI Framework

Parallel Reverse Mode Automatic Differentiation in C# for Custom Neural Network Development

Tensors and Dynamic neural networks in Python with strong GPU acceleration

An Open Source Machine Learning Framework for Everyone

Simulating and experimenting on single neurons

This project is part of the B.Tech degree in Electronics and Telecommunication Engineering at KIIT University. This project aims to implement a neural network on an FPGA.

Open standard for machine learning interoperability

Generating biologically informed neural networks

All of my Data Science & Machine Learning Projects

Note is a system for deep learning and reinforcement learning.

NeMo: a toolkit for conversational AI

Code, documentation, and tutorial for the DGD model trained on bulk RNA-Seq data.

High-efficiency floating-point neural network inference operators for mobile, server, and Web

A flexible, high-performance serving system for machine learning models

This is a simple artificial neural network, written in Julia.

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

💫 Industrial-strength Natural Language Processing (NLP) in Python

This is a work to improve molecular docking speed. Normally docking a ligand on a target protein is done with some very complex functions and it is often slow. This work uses Neural Networks to model ligands on target proteins to measure whether they are active or not.

Computer Vision and Robotics Library for AI

Model Compression Toolkit (MCT) is an open source project for neural network model optimization under efficient, constrained hardware. This project provides researchers, developers, and engineers advanced quantization and compression tools for deploying state-of-the-art neural networks.

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

On-device Neural Engine

Dataflow compiler for QNN inference on FPGAs

Introduction to artificial neural networks. Implementation of a multilayer perceptron that predicts whether a cancer is malignant or benign based on characteristics of cell nucleus.

Qdrant - Vector Database for the next generation of AI applications. Also available in the cloud https://cloud.qdrant.io/

C++ image processing and machine learning library with using of SIMD: SSE, AVX, AVX-512, AMX for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM.

Physics-Informed Neural networks for Advanced modeling

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.