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Applied Machine Learning Algorithms / Module 1

Module 1 lesson

Project Step: Algorithm Candidate Plan

Unit ID: AMLA-M01-U05 Estimated active time: 35-50 minutes

Classroom explanation

Now bring the module together. You are not fitting models yet. You are planning which models deserve attention.

This is a serious modelling skill. Good model builders reject many ideas before spending compute or trust on them.

Required plan

Create a short candidate plan with these sections:

  1. Problem statement.
  2. Data shape.
  3. Decision need.
  4. Baseline ladder.
  5. Candidate models to try.
  6. Models to reject for now.
  7. Metric and validation plan.
  8. Limitations.

Candidate reasoning

For every model you include, explain why it is reasonable.

For every model you reject, explain why it is not a good first choice. Rejection can be based on small data, too many missing values, poor interpretability fit, runtime risk, metric mismatch, or lack of evidence.

Practice

Draft your candidate plan in the algorithm comparison report template. Keep it to one page.

Takeaway

The first deliverable in an algorithm course is not a fitted model. It is a defensible plan for what deserves to be fitted.