Роль
Аплайнсы
Course stanford
The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes original (old) versions of Python, TensorFlow, and PyTorch, used in the course. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
Course
Tensorflow
Pytorch
Keras
Python
Cuda
Cudnn
Nvidia drivers
Course stanford
The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes original (old) versions of Python, TensorFlow, and PyTorch, used in the course. The software stack is optimized for running on CPU.
Course
Tensorflow
Pytorch
Keras
Python
Machine learning education
The pre-configured and ready-to-use runtime environment for the Open Machine Learning Course, 2018. It includes Python 3.6, TensorFlow 1.4, Keras 2, XGBoost, LightGBM and Vowpal Wabbit. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
Course
Cuda
Cudnn
Nvidia drivers
Machine learning education
The pre-configured and ready-to-use runtime environment for the Open Machine Learning Course, 2018. It includes Python 3.6, TensorFlow 1.4, Keras 2, XGBoost, LightGBM and Vowpal Wabbit. The software stack is optimized for running on CPU.
Course
Machine learning
A pre-configured and fully integrated software stack with Theano, a numerical computation library for Python, 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 NVidia GPU.
Theano
Python
Cuda
Cudnn
Nvidia drivers
Preset
Machine learning
A pre-configured and fully integrated software stack with Theano, a numerical computation library for Python, 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 NVidia GPU.
Theano
Python
Cuda
Cudnn
Nvidia drivers
Preset
Machine learning
A pre-configured and fully integrated software stack with Theano, a numerical computation library for Python, 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.
Theano
Python
Preset
Machine learning
A pre-configured and fully integrated software stack with Theano, a numerical computation library for Python, 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.
Theano
Python
Preset
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 NVidia GPU.
Mxnet
Python
Cuda
Cudnn
Nvidia drivers
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 NVidia GPU.
Mxnet
Python
Cuda
Cudnn
Nvidia drivers
Opencv
Preset