Exercise 1 — Predict powerkw and beat the baseline

Guided practice6 min
Time
20-30 min
You need
the kit, the venv active, data/features.csv from Week 4
Deliverable
the R2 of your six-column model and the file week05/power_actual_vs_predicted.png

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

Goal

NorthPeak's energy team wants to estimate the power a machine will draw from its load and its type. That is a regression: the target is a number. You start with the dumbest prediction, the mean. Then a line on load alone. Then a model with load, ambient temperature and the four type columns. At each step you measure MAE, RMSE and R2 on the last quarter. You end by reading the coefficients and drawing the predictions against the truth.

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

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This lesson is part of the “Week 5 — Regression, classification and evaluation” module

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