Machine learning

A pre-configured and fully integrated software stack with TensorFlow, an open source software library for machine learning, and the Python programming language. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on CPU.



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.

Aws ec2 Google cloud platform Digital ocean Microsoft azure Ibm bluemix Oracle cloud platform
Install on Linux

You can install the appliance directly on any Linux with 64-bit kernel (>=2.6.32). Run from the command line:

curl | 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 /jet/enter start.

How to use

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 mysql.

709 MB
Ubuntu 14.04

You can access the virtual machine via console or SSH:

Login: jet
Password: jet