Friday 13:30–15:00 in Tower Suite 1

Anomaly Detection

Nick Radcliffe

Audience level:
Intermediate

Description

Stochastic Solutions is producing a course on Anomaly Detection in Python for DataCamp. This workshop will give a preview of part of that course. Topics covered will include characterizing normality and abnormality, spotting anomalies by eye, building automated anomaly detectors over various kinds of data streams and types, and considerations for monitoring (false positives vs. false negatives).

Abstract

Stochastic Solutions is producing a course on Anomaly Detection in Python for DataCamp. This workshop will give a preview of part of that course. Topics covered will include characterizing normality and abnormality, spotting anomalies by eye, building automated anomaly detectors over various kinds of data streams and types, and considerations for monitoring (false positives vs. false negatives).

The workshop will include a number of exercises over sample data streams and will use a mixture of pure python, standard parts of the Scientific Python stack (numpy, pandas, matplotlib etc.), as well as the TDDA library.

No special knowledge will be assumed, but some familiary with the Python Scientific stack would be an advantage.

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