Fueling innovative software
July 15-18, 2019
Portland, OR
Anais Dotis

Anais Dotis
Developer Advocate, InfluxData

Website

Anais Dotis-Georgiou is a developer advocate at InfluxData with a passion for making data beautiful using data analytics, AI, and machine learning. She takes the data that she collects and does a mix of research, exploration, and engineering to translate the data into something of function, value, and beauty. When she’s not behind a screen, you can find her outside drawing, stretching, or chasing after a soccer ball.

Sessions

4:15pm4:55pm Thursday, July 18, 2019
Secondary topics:  AI Enhanced
Anais Dotis (InfluxData)
Average rating: ****.
(4.67, 3 ratings)
People are eager to use ML in anomaly-detection solutions, but it doesn't always make sense. Using statistical methods to detect one-off peaks in time series data is effective and efficient; however, statistical methods fail with contextual or collective anomalies. Anais Dotis-Georgiou explains how to use k-means for time series anomaly detection and when it makes sense to use machine learning. Read more.