NumPy & SciPy for GPU

A flexible framework of neural networks for deep learning

Introduction to Deep Neural Networks with Keras and Tensorflow

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

1st place solution

SCUDA is a GPU over IP bridge allowing GPUs on remote machines to be attached to CPU-only machines.

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

Safe rust wrapper around CUDA toolkit

GPU-accelerated Deep Learning on Windows 10 native

🚀🚀🚀 This repository lists some awesome public CUDA, cuda-python, cuBLAS, cuDNN, CUTLASS, TensorRT, TensorRT-LLM, Triton, TVM, MLIR, PTX and High Performance Computing (HPC) projects.

Minimal runtime core of Caffe, Forward only, GPU support and Memory efficiency.

Efficient, transparent deep learning in hundreds of lines of code.

OpenCV installation script with CUDA and cuDNN support

Hooked CUDA-related dynamic libraries by using automated code generation tools.

The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch

VGG-19 deep learning model trained using ISCX 2012 IDS Dataset

Debug your GPU, CUDA, and AI stacks across local, Docker, and CI/CD (CLI and MCP server)

Tutorial for using Singularity containers

PyTorch installation wheels for Jetson Nano

Script to remotely check GPU servers for free GPUs

TensorFlow wheels built for latest CUDA/CuDNN and enabled performance flags: SSE, AVX, FMA; XLA

Ubuntu 18.04 How to install Nvidia driver + CUDA + CUDNN + build tensorflow for gpu step by step command line

WICWIU(What I can Create is What I Understand)

Minimal Deep Learning library is written in Python/Cython/C++ and Numpy/CUDA/cuDNN.

Lightweight turnkey solution for AI

Archlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision

Allstate Kaggle Competition ML Capstone Project

darknet + ROS2 Humble + OpenCV4 + CUDA 11（cuDNN, Jetson Orin）

Tutorial on how to setup your system with a NVIDIA GPU and to install Deep Learning Frameworks like TensorFlow, Darknet for YOLO, Theano, and Keras; OpenCV; and NVIDIA drivers, CUDA, and cuDNN libraries on Ubuntu 16.04, 17.10 and 18.04.

A simple starting point for doing deep learning in Racket