Course fast ai

The pre-configured and ready-to-use runtime environment for the'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.


You can install the appliance on any new or existing Linux server, download and run it as a 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 supported hosting providers.

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.

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.

Download archive

You can download the archive, unpack it into the /jet directory, finish installation by executing the command /jet/enter /jet/own/bin/fasten and start the services by running /jet/enter start.

2.58 GB
Ubuntu 14.04
2.68 GB
2.83 GB
2.66 GB

You can access the virtual machine via console or SSH:

Login: jet
Password: jet


Main settings