Jonathan Bechtel
Jonathan is a data scientist at DSML Research where he oversees internal data science operations and outreach efforts by delivering seminars and public talks on the latest topics in Data Science and Machine Learning. In the past he's worked as a consultant for General Assembly, the NYPD, Amber Capital and Advent International to help them productionize their data and develop their internal analytics capabilities. He's the author of the KerasBeats deep learning package and has helped contribute to sktime and tensorflowjs. He has an MS in Analytics from Georgia Tech and resides in the NYC area. His particular passion is time series modeling since he believes it's the most practical way to align innovations in data science with business interests.
Sessions
skbase provides a meta-toolkit that makes it easy to build your own package that follows scikit-learn design patterns, e.g., parametric composable objects, and fittable objects. It contains a standalone BaseObject/BaseEstimator base class, base class templates to write your own base classes, templateable test classes and object checks, object retrieval and inspection, and more.