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1. Hands-on Time Series Anomaly Detection using Autoencoders, with Python

   Learn how to use Autoencoders to detect anomalies in time series data in a few lines of code.

   2024-08-21 Tags: time series, anomaly detection, autoencoders, python, machine learning, data analysis, production engineering, observatability by klotz
2. Stumpy: A Powerful and Scalable Python Library for Modern Time Series Analysis

   Stumpy is a Python library designed for efficient analysis of large time series data. It uses matrix profile computation to identify patterns, anomalies, and shapelets. Stumpy leverages optimized algorithms, parallel processing, and early termination to significantly reduce computational overhead.

   2024-08-01 Tags: time series, stumpy, data analysis, python, machine learning, pattern recognition, anomaly detection, production engineering by klotz

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