The following Jupyter notebook contains an implementation of Gaussian Process Regression Inspired from the description given in the MIT press publication Gaussian Processes for machine learning. (Page 37 of the pdf)
Implementation includes dynamic fitting abilities that allow a user to adjust a widget to observe the increased accuracy as we increase the number of points.
For more questions or details please email me at ccamano@sfsu.edu Code written Spring 2022