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