AppliedMath for LLMs3 hours

Implement ML Specific Math

Implement a portfolio-ready notebook experiment that proves you can use ML Specific Math, not just read about it.

Checklist progress0%

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Build brief

You are turning the ML Specific Math module into a concrete artifact. Keep the scope small, make the behavior visible, and leave enough notes that another learner can understand the result.

Requirements

  • Use at least two ideas from ML Specific Math.
  • Keep the implementation small enough to explain in five minutes.
  • Add three test cases or examples that show normal and edge behavior.
  • Write a short reflection that explains what broke and how you fixed it.

Deliverables

  • A runnable notebook cell sequence for ML Specific Math.
  • A short explanation of the math idea in plain language.
  • At least one visualization, table, or numerical sanity check.

Project checklist

Source lessons

Notes13-ML-Specific-Math/01-Loss-Functions/notes.mdOpenNotes13-ML-Specific-Math/02-Activation-Functions/notes.mdOpenNotes13-ML-Specific-Math/03-Normalization-Techniques/notes.mdOpenNotes13-ML-Specific-Math/04-Sampling-Methods/notes.mdOpenTheory Notebook13-ML-Specific-Math/01-Loss-Functions/theory.ipynbOpenExercises Notebook13-ML-Specific-Math/01-Loss-Functions/exercises.ipynbOpen
Run notebook

Milestones and skills

  1. 01Read the linked source lessons and note the key APIs or formulas.
  2. 02Sketch the smallest useful version of the notebook experiment.
  3. 03Build the core behavior before adding polish.
  4. 04Run the examples, notebook cells, or manual tests.
  5. 05Write the final explanation and mark the checklist complete.
ML Specific MathNumerical reasoningNotebook workflowPlanningTestingDebuggingExplanation