Content Moderation & Fraud Detection - Patterns in Industry
Explores five industry patterns for building robust content moderation and fraud detection systems using ML, including human-in-the-loop and data augmentation.
Explores five industry patterns for building robust content moderation and fraud detection systems using ML, including human-in-the-loop and data augmentation.
An overview of open-source tools for annotating time series data, including their features, maintenance status, and use cases.
Part 2 of a series on using Azure Anomaly Detector to identify unusual patterns in air quality sensor data for safety alerts.
A guide to implementing a simple anomaly detection system using only SQL and basic statistics, aimed at developers.