Setting Up TensorFlow and Jupyter (for the Brisbane.ai Tutorials)

The easiest way (I found) to setup TensorFlow on your system is by using a Docker install. Its advantages are that it just works out of the box, all dependencies are there and you can start building deep models within minutes! Warning: it does not allow you to accelerate the learning on a GPU though!!

So here are the steps required (on Mac):

  • Wait to download the image :)
  • You should be good to go!
    • You can test that by running python and type in the following;
    • >>> import tensorflow as tf
      >>> hello = tf.constant('Hello, TensorFlow!')
      >>> sess = tf.Session()
      >>> print(sess.run(hello))
    • To access the Jupyter notebook you need to forward the ports, you can do this by:
docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow

Happy hacking!

 

What is TensorFlow?

TensorFlow is an open source software library for machine learning across a range of tasks, and developed by Google to meet their needs around machine learning. More info: http://tensorflow.org

What is Docker?

Docker is an open platform for developers and sysadmins to build, ship, and run distributed applications, whether on laptops, data center VMs, or the cloud. More info: https://www.docker.com/

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One thought on “Setting Up TensorFlow and Jupyter (for the Brisbane.ai Tutorials)”

  1. How do I start the jupyter notebook such that I can use the notebook from the host machine? Ideally I would like to use docker to launch the container and start jupyter in a single command.

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