Deep reinforcement learning for de novo drug design: a ReLeaSe method execution on a Docker Environment
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Updated
Jan 12, 2023 - Dockerfile
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
Deep reinforcement learning for de novo drug design: a ReLeaSe method execution on a Docker Environment
Docker files used at Numeract
It contains the dockerfiles for the purpose of machine learning / deep learning research.
OpenCV environment built on anaconda gpu
A script that builds a docker container with CUDA & Ubuntu 18.04 and runs a little program through it to test the installation of OpenCV with (or without) CUDA support.
Step-by-step guidelines to develop and run PyTorch models in a dockerized container on NVIDIA GPUs
Ubuntu based Python container images, including CUDA images
Docker images for machine learning development environments using CUDA and PyTorch and for remote development via VSCode and SSH server
High performance computing Images with pycuda and tensorrt preinstalled
Ready-to-run Docker images containing Jupyter applications
Cuda 8.0, Latest stable Python, Dlib (with GPU support enabled)
Dockerfile for Chainer Development in VSCode
A set of Docker containers extensively used for both AI/HPC software development and deployment at Unum
NVidea CUDA base image on Ubuntu Linux, used to run Machine Learning
Data Science proto docker
nvidia docker image of cuquantum-python
(GPU accelerated) Multi-arch (linux/amd64, linux/arm64/v8) Julia docker images. Please submit Pull Requests to the GitLab repository. Mirror of
Created by Nvidia
Released June 23, 2007