Update Documentation

doc/src/gp-background.rst

@@ -10,9 +10,18 @@ Introduction
 
 This document focuses on the implementation details of some of the
 approaches used in
-`albatross <https://github.com/swift-nav/albatross>`__. For a deep dive
-in Gaussian processes you’re probably better off reading the book
-`Gaussian Processes for Machine Learning`_.
+`albatross <https://github.com/swift-nav/albatross>`__.
+
+If you're new to Gaussian processes you might consider watching these videos:
+
+`Machine Learning Lecture 26 "Gaussian Processes" Cornell CS4780 SP17 <https://www.youtube.com/watch?v=NegVuuHwa8Q>`__ (Kilian Weinberger)
+
+`Gaussian Process Basics <https://www.youtube.com/watch?v=NegVuuHwa8Q>`__ (David Mackay)
+
+And you might consider working through the `tutorials <https://github.com/swift-nav/albatross/tree/master/tutorials>`__ we've put together. These tutorials are in python notebooks (not c++) and are meant to serve as an educational tool to build intuition and introduce some of the tips and tricks you encounter when using GPs.
+
+For a deep dive in Gaussian processes, read the book `Gaussian Processes for Machine Learning <https://gaussianprocess.org/gpml/chapters/>`__.
+
 There are also a number of excellent introductions to Gaussian processes (see our :ref:`references`) here we assume some understanding of GPs and focus on describing the details of the implementations we use in `albatross`.
 
 ----------------

doc/src/index.rst

@@ -55,9 +55,11 @@ If you're using ``git`` you can run ``git submodule add https://github.com/swift
 Then make sure you've run ``git submodule update --recursive --init`` to be sure all the third party libraries required by albatross are also up to date.
 
 -----------------------
-Tests and Examples
+Tutorials, Tests, and Examples
 -----------------------
 
+We've put together a number of `tutorials <https://github.com/swift-nav/albatross/tree/master/tutorials>`__ which are meant to strengthen intuition around Gaussian processes.
+
 If you want to run the tests you can do so using ``cmake``,
 
 .. code-block:: bash
@@ -84,11 +86,11 @@ and plot the results (though this'll require a numerical python environment),
     :maxdepth: 1
 
     quickstart
+    gp-background
     1d-example
     temperature-example
     datasets
     split-apply-combine
-    gp-background
     gp-albatross
     crossvalidation
     tuning
@@ -109,8 +111,9 @@ The ensemble sampler was inspired by `emcee`_ which itself was inspired by the p
 Like this project? Want to get paid to help us apply it to our GNSS models? `Join us`_ at `Swift Navigation`_ !
 
 
-.. image:: https://bigmemes.funnyjunk.com/gifs/Albatross_408ca5_5434150.gif
+.. image:: https://media1.tenor.com/m/6gEAYtNJbUoAAAAd/albatross-monty-python.gif
    :align: center
+   :width: 200
 
 .. _`cross validation` : https://web.stanford.edu/~hastie/ElemStatLearn/
 .. _`scikit-learn` : https://github.com/scikit-learn/scikit-learn

tutorials/README.md

@@ -1,5 +1,7 @@
 # README
 
+These tutorials were designed with the goal of building intution and introduce some of the tips and tricks you encounter when using GPs. These tutorials can be thought of as the homework for a mini course in Gaussian processes. They consist of python notebooks which intentionally include gaps in the code. Fill in the sections marked `YOUR CODE HERE`. The first few tutorials might take several hours to work through, as they progress they should take less effort to complete.
+
 ## Setting up the environment
 
 ### Setup using conda