Python for Time Series Anomaly Detection

Python for Time Series Anomaly Detection:
“People say I’m strange, but does that make me an anomaly?”

Anomaly detection in time series data is an increasingly relevant need in a world full of streaming data and IoT devices. In this interactive talk, Josh Malina shows you how to spot anomalies in time series data using Python, Pandas and simple time series models. You will learn how to approach anomaly detection problems, prepare time series data for stationary models and understand exponentially weighted moving averages. You will also learn how to avoid some key time wasting gotchas that can lead you down the wrong path.

About the speaker:
Josh Malina is a Miami native and Machine Learning Engineer at American Express in Sunrise, Florida. He currently works on forecasting and anomaly detection problems related to time series data. Before joining AMEX, he worked as a machine learning engineer for a small government contractor in Charlottesville, Virginia. He can be reached at [masked] or [masked].

Bring a laptop to maximize participation.

Parking Instructions: Please note that the RSVP list (name only) will be shared with MDC for access to the parking garage. Enter the garage, Building 7, from the 5th Street entrance.