Detect anomalies using unsupervised learning
Implement using models like Isolation Forest/Local Outlier.
Detect maritime anomalies from AIS data
A sample fraud detection using unsupervised learning models
Monitor and analyze ADAS sensor data
Analyze NFL injuries from 2012-2015
Identify image anomalies by generating heatmaps and scores
MVTec website
Classify images as normal or anomaly
Identify and visualize anomalies in Excel data
A powerful AI-driven anomaly detection AP
Configure providers to generate a Stremio manifest URL
Detect anomalies in images
The Anomaly Detection App is an AI-powered tool designed to identify unusual patterns or deviations in time-series data. It leverages unsupervised learning to detect anomalies without requiring labeled data, making it ideal for uncovering hidden trends or unexpected behavior in datasets.
1. What types of data can the Anomaly Detection App handle?
The app is optimized for time-series data, commonly found in applications like sensor readings, financial transactions, and system metrics.
2. How accurate is the unsupervised learning model?
The app delivers high accuracy in identifying anomalies, though results may vary based on data quality and configuration.
3. Can the app handle real-time data streams?
Yes, the Anomaly Detection App supports real-time detection, enabling immediate insights from live data feeds.