AlexanderVNikitin/tsgm
Generation and evaluation of synthetic time series datasets (also, augmentations, visualizations, a collection of popular datasets) NeurIPS'24
This tool helps data scientists and machine learning engineers create realistic, synthetic time series data from existing datasets. You provide your real-world time series data, and it generates new, artificial time series that mimic the original's patterns and characteristics. This is useful for expanding small datasets or protecting sensitive information by using fake but statistically similar data.
218 stars. Available on PyPI.
Use this if you need to generate more time series data for training machine learning models, augment existing datasets, or evaluate the quality of synthetic data.
Not ideal if you are looking for a no-code solution or if your primary goal is simple data visualization rather than synthetic data generation.
Stars
218
Forks
24
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 10, 2026
Commits (30d)
0
Dependencies
12
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