Daniel studied Control Theory, Estimation Theory, and Signal Processing. He spent many years, as a Systems Engineer, analyzing, building, and testing gimbal stabilized platforms. Following that he spent a few years developing Signal Processing and Signal Communications libraries. Now he is passionate about creating clear, maintainable, and well tested code in reproducible systems. He cares about mentoring, teaching, and making complicated software accessible for the end user.
jupyterWith: Making Jupyter Reproducible
jupyterWith has made significant improvements this year towards maintainability and ease of use. This talk will discuss those improvements and how you can quickly start creating reproducible Jupyter notebooks.
Main track (Gym)