This notebook explores Gaussian Processes to find theoretical functions and then to use advance python machine learning libraries to
If you are unfamiliar with some of the concept covered in this tutorial it's recommended to read through the background reading below either as you go through the notebook or beforehand.
If you want a quick look at the contents inside the notebook before deciding to run it please view the md file generated (note some html code not fully rendered)
This notebook is designed to run on a laptop with no special hardware required therefore recommended to do a local installation as outline in the repository howtorun and jupyter_notebooks sections.
If you're already familiar with git, anaconda and virtual environments the environment you need to create is found in GP.yml and the code below to install activate and launch the notebook
conda env create -f GP.yml
conda activate GP
jupyter-notebook