Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Jupyter Notebook so that you can run and modify the code in your browser. What ...

This package is somewhat young – new features are being added and some (low-level) interfaces may be tweaked in the future, but things should be stable enough for general usage. Contributions welcome ...

Abstract: Exploiting machine learning techniques for analyzing programs has attracted much attention. One key problem is how to represent code fragments well for follow-up analysis. Traditional ...