A Docker image for PyTorch

Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.

AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charita…

Docker image with Jupyter, Pytorch and CUDA GPUs supports.

带 Web UI 的 Docker taiyi (太乙)，中文 Stable Diffusion WebUI 一键运行环境。

Deep Learning Docker Image

Machine Learning-Enabled ROS Docker Images

Fast.AI course complete docker container for Paperspace and Gradient

This repository contains a docker image that I use to develop my artificial intelligence applications in an uncomplicated fashion. Python, TensorFlow, PyTorch, ONNX, Keras, OpenCV, TensorRT, Numpy, Jupyter notebook... 🐋🔥

A step-by-step guide to setting up Nvidia GPUs with CUDA support running on Docker (and Compose) containers on NixOS host

Dockerfile for yolov5 inference on NVIDIA Jetson

A docker-based starter kit for machine learning via jupyter notebooks. Designed for those who just want a runtime environment and get on with machine learning. Docker Hub:

ROCm docker images with fixes/support for extra architectures, such as gfx803/gfx1010.

Anaconda3, Jupyter Notebook, OpenCV3, TensorFlow and Keras2 for Deep Learning🐳

Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.

A Docker image based on rocm/pytorch with support for gfx803(Polaris 20-21 (XT/PRO/XL); RX580; RX570; RX560) and Python 3.8

Dockerfile-s to build the images which power source{d}'s computing infrastructure.

Cross-compilation of PyTorch armv7l (32bit) for RaspberryPi OS

klab docker image building scripts

Everything about how to deploy projects on the cloud, run ML workloads on the HPC cluster and on the cloud and the efficient configuration and management of related collaborative platforms [e.g. container orchestration].