Merlion
tods
| Merlion | tods | |
|---|---|---|
| 5 | 3 | |
| 3,271 | 1,302 | |
| 1.0% | 2.7% | |
| 2.6 | 3.1 | |
| 6 days ago | 8 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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Merlion
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[podcast] Machine Learning for Time Series Intelligence
Aadyot Bhatnagar, is a Senior Research Engineer at Salesforce, and co-creator of Merlion an open source framework for applying machine learning on time series data.
- Merlion – A new time-series ML framework from Salesforce
- Salesforce research team introduces Merlion, an open-source Python library for time series intelligence
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[N] Salesforce Research Introduces ‘Merlion’, An Open-Source Machine Learning Library For Time Series Intelligence
5 Min Read | Paper | Code
tods
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Anomaly detection Algorithms
Sounds that OP is looking for time series anomaly detection, not multivariate. Perhaps https://github.com/datamllab/tods is an option,
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Unsupervised Anomaly Detection with Multivariate Time series
I suggest you try some AutoML library for anomaly detection, e.g.: https://github.com/datamllab/tods
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[P] [R] Luminaire: A hands-off Anomaly Detection Library
TODS
What are some alternatives?
luminaire - Luminaire is a python package that provides ML driven solutions for monitoring time series data.
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
anomstack - Anomstack - Painless open source anomaly detection for your metrics 📈📉🚀
cloud_benchmarker - Cloud Benchmarker automates performance testing of cloud instances, offering insightful charts and tracking over time.
OpenOOD - Benchmarking Generalized Out-of-Distribution Detection
airflow-provider-anomaly-detection - An airflow provider for anomaly detection.
anomaly-detection-resources - Anomaly detection related books, papers, videos, and toolboxes
paragon - A lightweight command line benchmarking utility
PyPOTS - A Python toolbox/library for reality-centric machine/deep learning and data mining on partially-observed time series with PyTorch, including SOTA neural network models for science analysis tasks of imputation, classification, clustering, forecasting & anomaly detection on incomplete (irregularly-sampled) multivariate TS with NaN missing values
timebasedcv - Time based splits for cross validation