jgaud/streamndr
Novelty detection for data streams in Python
This project helps identify brand new patterns or events as they appear within a continuous flow of data. It takes in real-time data observations and flags those that are significantly different from what has been previously observed. This is useful for data scientists or operations engineers who need to monitor systems for unexpected changes.
Use this if you need to automatically detect new, unknown patterns in a stream of incoming data, without prior examples of those novelties.
Not ideal if you need to classify data into predefined categories or detect anomalies that are already known.
Stars
13
Forks
1
Language
Python
License
BSD-3-Clause
Category
Last pushed
Mar 01, 2026
Commits (30d)
0
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