Machine learning education

The runtime environment constructor for the machine learning and deep learning tutorials and courses.

 default
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.
tensorflow:1.5.0, keras:2.0.2, python:2.7.14, jupyter_notebook:1.0.0, development_preset:1
Machine learning
A pre-configured and fully integrated software stack with TensorFlow, an open source software library for machine learning, 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.
tensorflow:1.5.0, python:2.7.14, development_preset:1
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 2.7 and TensorFlow 1.4.1. The software stack is optimized for running on CPU.
stanford-cs224n-course:2018, python:2.7.14
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 2, TensorFlow, and PyTorch. The software stack is optimized for running on CPU.
stanford-cs231n-course:1617spring, tensorflow:1.5.0, pytorch:0.3.0, keras:2.1.2, python:2.7.14