bartk97/NYC-Taxi-Anomaly-Detection
Final Project for the 'Machine Learning and Deep Learning' Course at AGH Doctoral School
This project helps operations managers or business analysts identify unusual patterns in time-series data, like passenger counts or sales figures. It takes historical data, broken down into regular time intervals, and highlights specific periods or data points that deviate significantly from typical trends. The output is a clear visualization of detected anomalies, helping you pinpoint unexpected events.
No commits in the last 6 months.
Use this if you need to automatically flag unexpected spikes or dips in your operational or business data that could indicate events like holidays, system outages, or special promotions.
Not ideal if your data lacks clear time ordering or if you need to predict future values rather than identify past anomalies.
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Jun 28, 2022
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