This is a presentation about Kalman filters for Computer Science Club.
There are some papers in the /docs folder, and some Jupyter notebooks mainly geared at
demonstrating issues about conjugate priors and a Kalman filter example in the
/jupyter folder. There are also presentation notes
for the presentation.
The notes refer to the Jupyter notebooks, which provide reinforcement of the concepts. Care was taken that these be visible in the repo since GitHub automatically launches a viewer for notebooks.
Alternately, the project can be cloned or forked and these notebooks run. One fun and appealing option is to run it on one of the new Amazon Machine Learning AMIs. Here is a really nice tutorial from Amazon on setting one up and using an SSH tunnel to avoid messing with configuring Jupyter to be secure. This gives you a lot of power very easily and cheaply while having the convenience of the familiar notebook environment.