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DISCOVERY STUDIO / MACHINE LEARNING / CLASS 11–12 ENRICHMENT
Machine Learning · EXPERIMENT 35

Model monitoring and drift

Data drift, performance tracking and retraining

Class 11–12 enrichment · Guided experience
VISUAL CONCEPT MAP · DATA

Model monitoring and drift

Read the shape of a dataset: compare values, discover patterns and ask better questions.

Input / evidence Processing Output / insight
DISTRIBUTION · PATTERN · TREND

Mission briefing

A deployed demand model becomes less accurate after a major change in customer behaviour.

Explore the concept, change an input, observe the result and explain what it means.

◈ MODEL PERFORMANCE CONSOLE LIVE METRICS
ACCURACY90%
PRECISION88%
RECALL92%
CONFUSION MATRIX · SELECT A CELL
PRED +
PRED −
ACTUAL +
ACTUAL −

Select a cell to understand the outcome.

✎ Observation log

Record what you observed, what changed and one limitation.

CBSEMOCK AI & ML Virtual Labs · Educational conceptual model. Outputs are illustrative, not evidence of a validated or trained production AI system. Confirm class-wise syllabus alignment before assessment.

Teacher review · Practical rubric

Suggested assessment framework. Teacher may adjust marks to suit the class and task.

Teacher rubric score: 4 / 10

Complete record includes student details, practical notes, experiment title, date and teacher rubric. Existing lab-specific notebook and activities are retained.

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