Automatically Find Patterns & Anomalies from Time Series or Sequential Data - Sean Law
In this talk, you’ll learn of a brand new and scalable approach to explore time series or sequential data. If anybody has ever asked you to analyze time series data and to look for new insights then this is definitely the open source tool that you’ll want to add to your arsenal.
![[30] Modern Time Series Analysis with STUMPY (Sean Law)](https://i.ytimg.com/vi/XKNdXN-Jfmo/hqdefault.jpg?sqp=-oaymwEjCNACELwBSFryq4qpAxUIARUAAAAAGAElAADIQj0AgKJDeAE=&rs=AOn4CLAJwSVNKpgja7mkPJCvnhJWPs1OqA)
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[30] Modern Time Series Analysis with STUMPY (Sean Law)
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Time Series data Mining Using the Matrix Profile part 1
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The EM Algorithm Clearly Explained (Expectation-Maximization Algorithm)
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Kishan Manani - Feature Engineering for Time Series Forecasting | PyData London 2022
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The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
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Detecting outliers and anomalies in realtime at Datadog - Homin Lee (OSCON Austin 2016)
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Anomaly Detection 101 - Elizabeth (Betsy) Nichols Ph.D.
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Sean Law - Modern Time Series Analysis with STUMPY - Intro To Matrix Profiles | PyData Global 2020
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Sean Law - STUMPY: Modern Time Series Analysis with Matrix Profiles | SciPy 2024
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Eamonn Keogh - Finding Approximately Repeated Patterns in Time Series
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The KL Divergence : Data Science Basics
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Anomaly Detection: Algorithms, Explanations, Applications
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Dynamic time warping 1: Motivation
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TypeScript in Express – TypeScript Tutorial
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Aileen Nielsen - Irregular time series and how to whip them
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Time Series Forecasting with XGBoost - Advanced Methods
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But what is quantum computing? (Grover's Algorithm)
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The Bayesians are Coming to Time Series
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Anomaly Detection using Neural Networks - Dean Langsam
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