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Anomaly Detection in The Opioid Files - Watch on Demand

Dataiker Alumni
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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:

  1. What's your experience with Anomaly Detection?
  2. Any best practices to share, or pitfalls to avoid?
  3. 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. 

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