stepanovd / ts_anomaly_detection_course Goto Github PK

This repository including notebooks with examples about timeseries anomaly detection.

YouTube course https://www.youtube.com/watch?v=92EF4vqaBSE&list=PL7GGfr9mTeYWniRK11xuFsEky07oUQ_tX&index=2

Our dataset is timeseries of food retail:

• ou - index of shop
• datetime - ISO format of date and hour
• cheques - count of payment
• rto - revenue in rubles
• n_sku - count of lines in bills
• cnt - number of items
• cashnum - number of opened windows while hour

We explore few approaches for anomaly detection in 1-D timeseries such as:

1. statistical anomalies based on normal distribution
2. forecasting method - detection anomalies as error of forecast
3. classification method Isolation Forest
4. clusterization method K-means
5. K Nearest Neighbors

Also we explore few approaches for anomaly detection in Multi dimensions timeseries based on PyOD library.