Exercise 3 — Drift report: Q1 vs Q4

Guided practice5 min
Time
30 min
You need
the kit, the venv, python data/make_dataset.py done; no Ollama today
Deliverable
week13/drift_report.csv and the name of the sensor that drifted

The lab kit of the course: https://github.com/hrhouma2/aiopsatlas-ml-data-diagnostics-labs-en

Goal

The fault model of Week 6 learned on readings from before October. Has the data changed since? You compare the first quarter (January to March) with the last quarter (October to December) of readings.csv, sensor by sensor: mean, standard deviation and a PSI. Then you check whether the link between the sensors and fault_next_7d moved. You will name the sensor that drifted, explain why, and say whether that is a reason to retrain.

Preview — the rest of the lesson is for enrolled readers.

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This lesson is part of the “Week 13 — Observability and model reliability” module

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