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If you are utilizing this work in any way, please cite the following paper as appropriate: ``` Martin Valdez-Vivas, Nicholas Stanisha, Benoit Rostykus, Juanyan Li, and Amit Pahwa. 2024. An Integrated Framework for Forecasting and Anomaly Detection in the Data Lakehouse. In Proceedings of KDD ‘24 (KDD’24). ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn (submitted) ``` *Disclaimer: this repository is intended for demonstration purposes only and is not a maintained OSS product.* Notebooks The notebooks directory contains executable scripts to recompute forecasting & anomaly detection benchmarks, and also to demonstrate the execution of detectors and event generators as described in the paper. 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