Data Science in Python - Real-Time Anomaly Detection

February's Python North West will be a data science talk from Tim Butters, specifically on the topic of Real-Time Anomaly Detection and Time Series Analysis.

Tim is a senior data scientist working in R&D in Manchester. While the topics covered in his talk are quite advanced in places, the talk should be accessible to anyone with any level of interest in doing data science in Python.

Tim said this about his talk:

"Industrial manufacturing and processing sites produce vast quantities of data every day. Sensors relay data to complex automated control and optimisation systems to ensure efficient and safe operation. With the recent prevalence of data science, analytics companies have started to explore ways in which this data can be used in other ways, for example, automatically identifying equipment issues. However, this is a complex task due to the ever-changing conditions on site, complex levels of data abstraction, and the number of time series involved.

In this talk we will discuss how to detect anomalies in time series, and extend on that to cover solutions that automatically adapt when process conditions change. This anomaly detection system, all implemented in Python, draws on a number of useful statistical analysis methods which will be of interest to anyone interested in doing data science in Python. We will finish by showing a real-life example from the process industry."

As with our last two meetings this one will be held at Federation House who require that I provide a list of attendees the day before the talk, so please try to RSVP by 5pm on the 20th Feb.

Hope to see you there!