name: notebook-patterns
description: Pedagogical patterns for enriching notebooks (GameTheory model). Use when adding interpretations, structuring notebooks, or creating educational content in Jupyter notebooks.
Notebook Enrichment Patterns
Standard Header (all notebooks)
# Series-N-Title
**Navigation** : [Index](README.md) | [<< Precedent](Series-N-1.ipynb) | [Suivant >>](Series-N+1.ipynb)
## Objectifs d'apprentissage
A la fin de ce notebook, vous saurez :
1. ...
2. ...
### Prerequis
- Python 3.10+ / .NET 9.0
- Cle API configuree (.env)
### Duree estimee : XX minutes
Interpretation Pattern (after significant code output)
### Interpretation : [Concept Name]
**Sortie obtenue** : [Brief summary of output]
| Aspect | Valeur | Signification |
|--------|--------|---------------|
| ... | ... | ... |
**Points cles** :
1. ...
2. ...
> **Note technique** : [Detail if relevant]
Positioning Rules (CRITICAL)
- Introduction cells go BEFORE the code they introduce (future tense)
- Interpretation cells go AFTER the code output they analyze (past tense)
- Transition cells go BETWEEN sections
- Conclusion cells go at the END of a section or notebook
Cell Insertion Strategy
- Work from BOTTOM to TOP to avoid index shifting
- Use
cell_id (not index) for NotebookEdit insert reference
- Verify position immediately after each insertion
- One cell at a time - never batch inserts
Domain-Specific Vocabulary
| Domain |
Key Terms |
| ML |
accuracy, loss, epoch, overfitting, cross-validation |
| Probas/Infer |
prior, posterior, distribution, inference, factor graph |
| GameTheory |
Nash equilibrium, Shapley value, dominant strategy |
| SymbolicAI |
satisfiability, resolution, proof, axiom, theorem |
| GenAI |
prompt, tokens, embedding, fine-tuning, hallucination |
| Optimization |
fitness, generation, mutation, crossover, convergence |
Code/Markdown Ratios
| Level |
Code |
Markdown |
Visualizations |
| Intro |
35-40% |
55-60% |
min 3 |
| Intermediate |
45-50% |
45-50% |
min 4 |
| Advanced |
55-60% |
35-40% |
min 2 |
Quality Checklist
By