STUMPY: A Powerful and Scalable Library for Modern Time Series Analysis - Sean Law

Traditional time series analysis techniques have found success in a variety of data mining tasks. However, they often require years of experience to master and the recent development of straightforward, easy-to-use analysis tools has been lacking. We address these needs with STUMPY, a scientific Python library that implements a novel yet intuitive approach for discovering patterns, anomalies, and other insights from any time series data. This presentation will cover the necessary background needed to follow the live interactive demo, requires no prior experience, and promises a simple, powerful, and scalable time series analysis library that will complement your current toolset.

Bio:
Sean Law is a senior applied scientific researcher and data scientist currently working with a multi-talented Exploration Lab team (formerly, Advanced Technology) and serves as an advisor on an enterprise A.I. Council at TD Ameritrade. He has experience producing cutting edge methodologies, building high-performance predictive models, and developing rapid prototypes.

Additionally, Sean co-organizes the monthly PyData Ann Arbor data science meetup and is also the creator and core maintainer of STUMPY, a powerful and scalable open source Python library that can be used for a variety of time series data mining tasks.

Видео STUMPY: A Powerful and Scalable Library for Modern Time Series Analysis - Sean Law канала Chicago Python Users Group