A pre-configured and fully integrated minimal runtime environment with TensorFlow, an open source software library for machine learning, Keras, an open source neural network library, Jupyter Notebook, a browser-based interactive notebook for programming, mathematics, and data science, and the Python programming language. The stack is built with the Intel MKL and MKL-DNN libraries 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.
You can install the appliance directly on any Linux with 64-bit kernel (>=2.6.32). Run from the command line:
curl http://it.aise.ai/appliances/aise/tensorflow18_keras21_python36_mkl_notebook-180526/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:
Config: | /jet/etc/jupyter_notebook/jupyter_notebook_config.py Address: | http://server_address:8888 Password: | empty