The aim of this workshop is to provide an introduction to GP, BGPLVM and MRD. It also includes a code review to implement these models in Python. Contents of the workshop:

• Theory
  • Gaussian Processes
  • Gaussian Process Latent Variable Model
  • Bayesian Gaussian Process Latent Variable Model
  • Manifold Relevance Determination
• Practical
  • GPy Library
  • GPflow Library

This repository contains the presentation PDFs and Ipython notebooks with exercises on GPy.

• Install Docker by running the following command:

sudo apt-get install -y docker.io

• Clone the docker image for the workshop

sudo docker pull buntyke/gp-workshop

• Run the docker image for the workshop

sudo docker run -it -p 8888:8888 buntyke/gp-workshop

• The command outputs text that includes an URL like this:

Copy/paste this URL into your browser when you connect for the first time, to login with a token:
http://localhost:8888/?token=b8dbd6e58f68195b150bfcc69751bd97ddc20c097767d100

Copy the url and paste in the web browser to start the Ipython session.

• Download docker-toolbox from this link.
• Install docker-toolbox and agree with all options. This will install Docker-Quickstart-Terminal.
• Open the Docker-Quickstart-Terminal application which opens a terminal.
• Download the docker image with this command:

docker pull buntyke/gp-workshop

• Run the docker image with this command:

docker run -it -p 8888:8888 buntyke/gp-workshop

The command outputs text that includes an URL like this:

Copy/paste this URL into your browser when you connect for the first time, to login with a token:
http://localhost:8888/?token=b8dbd6e58f68195b150bfcc69751bd97ddc20c097767d100

• Open a powershell and run the following command:

docker-machine.exe ip default

The command outputs an IP like this:

192.168.99.100

• Replace localhost with the IP and paste URL above in the web browser to start Ipython session:

http://192.168.99.100:8888/?token=b8dbd6e58f68195b150bfcc69751bd97ddc20c097767d100