Week 02 · overview

Week 2: Perceptrons and Layered Networks

A neural network is not a digital brain or a box that “thinks.” It is a parameterized calculation. This week begins with Microsoft's pinned perceptron and multilayer-perceptron chapters, then slows the mechanism down enough to inspect every number.

DayRoleEvidence
1Lesson 1: PerceptronTrace inputs, weights, bias, score, and threshold
2Lesson 2: Multilayer perceptronExplain why layers and nonlinear activations matter
3InvestigationCompare four binary cases and locate a linear boundary
4LabBuild and test a two-layer XOR calculation
5Assessment + ReflectionDefend one claim and state the model boundary

Learning contract

By the end of the week, you will be able to:

  • calculate a perceptron output from declared inputs and parameters;
  • distinguish training from inference;
  • explain why one linear threshold cannot represent XOR;
  • trace a small layered network without calling it magic; and
  • use a complete four-case test table to support or reject a claim.

Evidence target

Your Layered Network Test Record must preserve all four XOR inputs, both hidden-unit results, the final output, the expected output, and one bounded conclusion. The record proves only that the supplied deterministic calculation matches four supplied cases.

Use no personal or sensitive data. The investigation and Lab are hand-checkable local calculations; they do not train a live model or contact an AI service.

The complete Microsoft source repository—including notebooks, code, images, assignments, translations, and credits—remains preserved in the local upstream/ mirror. Review the source record.

Chapter question

How does Perceptrons and Layered Networks change what evidence a student should trust?

What you will understand

You will connect the named mechanism to the evidence it can and cannot support.

What you will do

You will inspect supplied cases, trace the important calculation, and test one bounded claim.

What you will produce

You will produce the week evidence record named in the Lab or reflection.

How the week connects

This week carries the previous AI mechanism forward into a stricter evidence check.

Key vocabulary

mechanism; evidence; boundary; test; claim

Approximate time

Five class meetings at about 210 instructional minutes total.

Final evidence required

Submit the completed week record with at least two exact labels from the artifact.