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.
You can install the appliance on any new or existing Linux server, download and run virtual machine, use it as a base image for Docker or Vagrant, or launch it with a new cloud platform instance, VPS or dedicated server for a supported hosting providers.
You can install the appliance directly on any Linux with 64-bit kernel (>=2.6.32). Run from the command line:
curl http://jetware.io/appliances/jetware/course_udacity_nd009t_2018_python2_cuda8-180209/file/installer:tgz/setup | sh
You’ll be asked to execute some operations as root via
sudo during the installation.
Or download archive, unpack it to
/jet directory, install appliance executing the command
/jet/enter /jet/own/bin/fasten and start the services by running
To enter the runtime environment or to execute a command inside the runtime environment you can use the utility
/jet/enter. If no arguments are present, the standard shell will be executed inside the runtime environment. You can specify a command as an argument, it will be executed inside the runtime environment.
For example, to start all services in the runtime environment you can do
/jet/enter start. To execute a mysql client you can do
/jet/enter mysql; or run first
/jet/enter, and than run from the new command line
You can access the virtual machine via console or SSH: