One Analysis a Day Keeps Anomalies Away - Detecting and Analyzing Data Anomalies
Offered By: EuroPython Conference via YouTube
Course Description
Overview
Explore Python techniques for data observability and anomaly detection in this 28-minute conference talk from EuroPython 2024. Learn methods to monitor data health, spot anomalies in multivariate time series, and perform efficient root cause analysis. Discover strategies for distinguishing true anomalies from data drift and setting up effective monitoring systems. Gain insights on turning data challenges into business opportunities, making this talk valuable for machine learning enthusiasts and those focused on maintaining data quality.
Syllabus
One analysis a day keeps anomalies away! — Madalina Ciortan
Taught by
EuroPython Conference
Related Courses
How to Detect Silent Failures in ML ModelsData Science Dojo via YouTube Dataset Management for Computer Vision - Important Component to Delivering Computer Vision Solutions
Open Data Science via YouTube Testing ML Models in Production - Detecting Data and Concept Drift
Databricks via YouTube Ekya - Continuous Learning of Video Analytics Models on Edge Compute Servers
USENIX via YouTube Building and Maintaining High-Performance AI
Data Science Dojo via YouTube