dream-faster/fold
🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.
This tool helps data scientists and machine learning engineers rapidly build, test, and deploy time-series forecasting models. It takes historical time-series data and model configurations, producing predictions and performance metrics up to 10 times faster than traditional methods. Its primary users are professionals who need to develop and maintain predictive models for dynamic, real-world data.
102 stars. No commits in the last 6 months.
Use this if you need to quickly develop and evaluate complex, adaptive time-series models that can update as new data becomes available.
Not ideal if you are looking for a fully documented, user-friendly library with active support, as this is an internal project with outdated documentation.
Stars
102
Forks
6
Language
Python
License
—
Category
Last pushed
Feb 29, 2024
Commits (30d)
0
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