Jonathan Bechtel
Jonathan is the principal data scientist for the Data Science and Machine Learning Research Group, which is a consultancy that allows ambitious academics to do transformative work in the commercial sector. He's also a contributor and community council member for SKTime.
In the past he's worked with organizations such as General Assembly, NYPD, Amber Capital and Advent International to assist them with their data science needs.
Sessions
Traditional time series models such as ARIMA and exponential smoothing have typically been used to forecast time series data, but the use of machine learning methods have been able to set new benchmarks for accuracy in high profile forecasting competitions such as M4 and M5.
However, the use of machine learning models can easily lead to inferior results under common conditions. This talk is a discussion of how each of these methods can be used to model time series data, and demonstrate how SKTime provides a unified framework for implementing both families of techniques.