Version
Keras
keras:2.0.2
Module
Version
2.0.2
Other branches
Role
Description

Keras, an open source neural network library written in Python.

Machine learning education

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

Machine learning education

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

Course udacity
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.
udacity-nd009t-course:2018, python:3.5.4, cuda:8.0.61, cudnn:5.1.10, cuda_only-nvidia_drivers:384.111
Course udacity
The pre-configured and ready-to-use runtime environment for the Udacity's Machine Learning Engineer Nanodegree program (nd009t). It includes Python 2.7, TensorFlow 1.0.0 and Keras 2.0.2. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
udacity-nd009t-course:2018, python:2.7.14, cuda:8.0.61, cudnn:5.1.10, cuda_only-nvidia_drivers:384.111
Course udacity
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.
udacity-nd009t-course:2018, python:3.5.4
Course udacity
The pre-configured and ready-to-use runtime environment for the Udacity's Machine Learning Engineer Nanodegree program (nd009t). It includes Python 2.7, TensorFlow 1.0.0 and Keras 2.0.2. The software stack is optimized for running on CPU.
udacity-nd009t-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 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.
stanford-cs231n-course:1617spring, tensorflow:1.0.1, pytorch:0.1.11, keras:2.0.2, python:3.5.4, cuda:8.0.61, cudnn:5.1.10, cuda_only-nvidia_drivers:384.111