Let's implement a Kalman Filter for tracking in Python.
00:00 Intro
00:09 Set up virtualenv and dependencies
01:40 First KF class
04:16 Adding tests with unittest and pytest
08:44 Using type annotations
09:25 Implement predict()
21:00 Plotting and interpreting mean and uncertainties
28:30 Implement update()
34:27 Plotting dynamics between predict() and update() steps
43:14 Robustifying the code
47:50 Wrap up
Playlist: https://www.youtube.com/playlist?list=PLvKAPIGzFEr8n7WRx8RptZmC1rXeTzYtA
Code: https://github.com/cbecker/kalman_python_cpp
