Package
Appliances
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.
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.
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 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.
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.
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 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 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.
The pre-configured and ready-to-use runtime environment for the MIT 6.S094 course: Deep Learning for Self-Driving Cars, 2017. It includes Python 2.7, TensorFlow 0.12.1 and OpenCV 3.3.0. 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 MIT 6.S094 course: Deep Learning for Self-Driving Cars, 2017. It includes Python 2.7, TensorFlow 0.12.1 and OpenCV 3.3.0. The software stack is optimized for running on CPU.
The pre-configured and ready-to-use runtime environment for the Fast.ai's courses Practical Deep Learning for Coders, 2017 edition, part 2. It includes Python 2.7, Theano 0.8, TensorFlow 1.0 and Keras 1.1. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
