The pre-configured and ready-to-use runtime environment for the Udacity's Deep Learning Nanodegree Foundation program (nd101). It includes Python 3.5, TensorFlow 1.0.0 and tflearn 0.30. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.

The pre-configured and ready-to-use runtime environment for the Udacity's Deep Learning Nanodegree Foundation program (nd101). It includes Python 3.5, TensorFlow 1.0.0 and tflearn 0.30. The software stack is optimized for running on CPU.

The pre-configured and ready-to-use runtime environment for the Udacity's Machine Learning Engineer Nanodegree program (nd009t). It includes Python 3.5, TensorFlow 1.0.0 and Keras 2.0.2. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.

The pre-configured and ready-to-use runtime environment for the Udacity's Machine Learning Engineer Nanodegree program (nd009t). It includes Python 3.5, TensorFlow 1.0.0 and Keras 2.0.2. The software stack is optimized for running on CPU.

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.

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.