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Vijay Janapa Reddi
2026-03-08 14:23:12 -04:00
parent e83d181ce8
commit f7d834b0c9
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book/quarto/contents/vol1/ml_systems/ml_systems.qmd
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@@ -781,10 +781,28 @@ The TinyML lighthouse, **Keyword Spotting (KWS)**\index{Keyword Spotting (KWS)!T
```{python}
#| echo: false
#| label: doorbell-scorecard
# ┌─────────────────────────────────────────────────────────────────────────────
# │ DOORBELL SCORECARD (FIGURE)
# ├─────────────────────────────────────────────────────────────────────────────
# │ Context: Lighthouse model evaluation
# │ Goal: Visualize the radar plot scorecard for the smart doorbell application
# └─────────────────────────────────────────────────────────────────────────────
# ┌── 1. CANVAS ────────────────────────────────────────────────────────────────
# │ Initialize the visualization modules
import mlsysim
import matplotlib.pyplot as plt
# ┌── 2. ARRAYS ────────────────────────────────────────────────────────────────
# │ Load the evaluation data for the Doorbell scenario
doorbell_eval = mlsysim.Applications.Doorbell.evaluate()
# ┌── 3. RENDER ────────────────────────────────────────────────────────────────
# │ Plot the radar scorecard using the mlsysim helper
fig, ax = mlsysim.plot_evaluation_scorecard(doorbell_eval)
# ┌── 4. DECORATE ──────────────────────────────────────────────────────────────
# │ Display the figure
plt.show()
```