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ML Workbench for TensorFlow

By: netCubed Latest Version: v1.2.1
Linux/Unix
Linux/Unix

Product Overview

Ubuntu 18.04 with Jupyter, JupyterLab, TensorBoard and preconfigured conda environments for Tensorflow 1.14.0 and TensorFlow 2 Beta including the latest matching versions of CUDA 10.0 and cuDNN 7.6.1 for GPU-accelerated computing. There is no need for an SSH session to launch a notebook. All services, including TensorBoard and the Ubuntu MATE desktop, can be accessed through the browser. Check out the video to see how to start training your first model on a GPU in less than 5 minutes.

Additionally, this environment provides a full-featured Ubuntu MATE desktop environment and direct console access through the browser with the latest versions of Google Chrome, Visual Studio Code and Docker (including the NVIDIA Container Runtime).

The Machine Learning Workbench puts a focus on security. All communication to the instance is encrypted, launching and accessing the Jupyter Notebook requires username and password authentication.

Version

v1.2.1

Operating System

Linux/Unix, Ubuntu 18.04

Delivery Methods

  • Amazon Machine Image

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