For the first virtual event of the New York Dataiku user group, @pmasiphelps (Lead Data Scientist at Dataiku) presented an anomaly detection project in Dataiku DSS, based on the data in The Washington Post’s The Opioid Files.
Anomaly detection is a step in data mining that identifies data points, events, and/or observations that deviate from a dataset's normal behavior. Anomalous data can indicate critical incidents, such as a technical glitch, or potential opportunities, for instance a change in consumer behavior.
Be sure to join the New York user group to be informed of upcoming events and chat with New York based DSS users!
We're wondering:
- What's your experience with Anomaly Detection?
- Any best practices to share, or pitfalls to avoid?
- What is the most interesting dataset you have ever worked with?
Comment below!
Please note: The dataset that is used in this presentation is the publicly available data presented by The Washington Post.