Аплайнсы
Course stanford
The pre-configured and ready-to-use runtime environment for the Stanford's CS224n course: Natural Language Processing with Deep Learning. It includes Python 3.6 and TensorFlow 1.4.1. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
Course
Python
Cuda
Cudnn
Nvidia drivers
Course stanford
The pre-configured and ready-to-use runtime environment for the Stanford's CS224n course: Natural Language Processing with Deep Learning. It includes Python 3.6 and TensorFlow 1.4.1. The software stack is optimized for running on CPU.
Course
Python
Course stanford
The pre-configured and ready-to-use runtime environment for the Stanford's CS20 course: Tensorflow for Deep Learning Research. It includes Python 3.6 and TensorFlow 1.4.1. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
Course
Cuda
Cudnn
Nvidia drivers
Course stanford
The pre-configured and ready-to-use runtime environment for the Stanford's CS20 course: Tensorflow for Deep Learning Research. It includes Python 3.6 and TensorFlow 1.4.1. 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
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 software stack is optimized for running on CPU.
Course
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 latest versions of Python 3, TensorFlow, and PyTorch. 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 latest versions of Python 3, TensorFlow, and PyTorch. 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