A pre-configured and fully integrated minimal runtime environment with TensorFlow, an open source software library for machine learning, Keras, an open source neural network library, Jupyter Notebook, a browser-based interactive notebook for programming, mathematics, and data science, and the Python programming language. The stack is optimized for running on CPU.

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.

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.

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.

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.

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.

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.