Package
Appliances
A pre-configured and fully integrated minimal runtime environment with TensorFlow, an open source software library for machine learning, 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, 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 PyTorch, an open source machine learning 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 CS224n course: Natural Language Processing with Deep Learning. 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 CS224n course: Natural Language Processing with Deep Learning. 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 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 Fast.ai's courses Practical Deep Learning for Coders, 2018 edition, part 1. It includes Python 3.6 and PyTorch 0.3.0. 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 Fast.ai's courses Practical Deep Learning for Coders, 2018 edition, part 1. It includes Python 3.6 and PyTorch 0.3.0. The software stack is optimized for running on CPU.