That's a fair question. My goal with the site was to make as much material available for free as possible, and the core linear Kalman filter content is indeed freely accessible.
The book goes further into topics like tuning, practical design considerations, common pitfalls, and additional examples. But there are definitely many good free resources out there, including the one you linked.
Huge +1 for Roger Labbe's book/jupyter notebooks. They really helped me grok Kalman filters but also the more general problem and the various approaches that approximate the general problem from different directions.
There are not many good resources on Kalman filters. In fact, I have found a single one that I'd consider good. This is someone who has spent a lot of time to newly understand Kalman filters.
The book goes further into topics like tuning, practical design considerations, common pitfalls, and additional examples. But there are definitely many good free resources out there, including the one you linked.