Appliances
Course mit
The pre-configured and ready-to-use runtime environment for the MIT 6.S094 course: Deep Learning for Self-Driving Cars, 2017. It includes Python 2.7, TensorFlow 0.12.1 and OpenCV 3.3.0. The software stack is optimized for running on CPU.
Course
Course fast ai
The pre-configured and ready-to-use runtime environment for the Fast.ai's courses Practical Deep Learning for Coders, 2018 edition, part 1. It includes Python 3.6 and PyTorch 0.3.0. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
Course
Cuda
Cudnn
Nvidia drivers
Machine learning
A pre-configured and fully integrated software stack with MXNet, an open-source deep learning framework, and Python 3.6. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on CPU.
Mxnet
Python
Opencv
Preset
Machine learning
A pre-configured and fully integrated software stack with MXNet, an open-source deep learning framework, and Python 2.7. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on CPU.
Mxnet
Python
Opencv
Preset
Caffe2
A pre-configured and fully integrated software stack with Caffe2, a lightweight, modular, and scalable deep learning framework. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on CPU.
Caffe2
Python
Opencv
Preset
Caffe
A pre-configured and fully integrated software stack with Caffe deep learning framework and Python 3.6. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on CPU.
Caffe
Python
Opencv
Preset
Caffe
A pre-configured and fully integrated software stack with Caffe deep learning framework and Python 2.7. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on CPU.
Caffe
Python
Opencv
Preset