using-neural-architectures

# Using Neural Architectures: Architecture Selection Router

<CRITICAL_CONTEXT>
Architecture selection comes BEFORE training optimization. Wrong architecture = no amount of training will fix it.

This meta-skill routes you to the right architecture guidance based on:

- Data modality (images, sequences, graphs, etc.)
- Problem type (classification, generation, regression)
- Constraints (data size, compute, latency, interpretability)

Load this skill when architecture decisions are needed.
</CRITICAL_CONTEXT>

## When to Use This Skill

Use this skill when:

- ✅ Selecting an architecture for a new problem
- ✅ Comparing architecture families (CNN vs Transformer, RNN vs Transformer, etc.)
- ✅ Designing custom network topology
- ✅ Troubleshooting architectural instability (deep networks, gradient issues)
- ✅ Understanding when to use specialized architectures (GNNs, generative models)

DO NOT use for:

- ❌ Training/optimization issues (use training-optimization pack)
- ❌ PyTorch implementation details (use pytorch-engineering pack)
- ❌ Production deployment (use ml-production pack)

**When in doubt:** If choosing WHAT architecture → this skill. If training/deploying architecture → different pack.

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## How to Access Reference Sheets

**IMPORTANT**: All reference sheets are located in the SAME DIRECTORY as this SKILL.md file.

When this skill is loaded from:
  `skills/using-neural-architectures/SKILL.md`

Reference sheets like `cnn-families-and-selection.md` are at:
  `skills/using-neural-architectures/cnn-families-and-selection.md`

NOT at:
  `skills/cnn-families-and-selection.md` ← WRONG PATH

When you see a link like `[cnn-families-and-selection.md](cnn-families-and-selection.md)`, read the file from the same directory as this SKILL.md.

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## Core Routing Logic

### Step 1: Identify Data Modality

**Question to ask:** "What type of data are you working with?"

| Data Type | Route To | Why |
|-----------|----------|-----|
| Images (photos, medical scans, etc.) |