c4d1524793
- Created full CAPVED folder with METADATA, 01-06 phases, and SUMMARY - Updated _INDEX.yml with new task entry - Documents: Polygon data loading, MySQL→PostgreSQL migration, 12 attention models Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
61 lines
1.6 KiB
Markdown
61 lines
1.6 KiB
Markdown
# 03-PLANEACION - ML Data Migration & Model Training
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## Fecha: 2026-01-25
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## Fase: PLANEACION (P)
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## Estado: COMPLETADA
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---
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## 1. Plan de Ejecucion
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### Fase 1: Preparacion Ambiente Python
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1. Crear venv en WSL: `~/venvs/data-service/`
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2. Instalar dependencias: aiohttp, asyncpg, pandas, numpy, python-dotenv
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### Fase 2: Carga de Datos
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1. Crear script `fetch_polygon_data.py`
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2. Configurar API key de Polygon
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3. Ejecutar carga para 6 tickers x 365 dias
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4. Validar datos insertados
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### Fase 3: Migracion ML Engine
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1. Crear `apps/ml-engine/src/data/database.py`
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2. Implementar PostgreSQLConnection con metodos:
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- `get_ticker_data()`
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- `execute_query()` con traduccion MySQL→PostgreSQL
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3. Actualizar `config/database.yaml`
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4. Crear `.env` con credenciales
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### Fase 4: Entrenamiento Modelos
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1. Instalar dependencias ML: xgboost, scikit-learn, joblib
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2. Ejecutar `train_attention_models.py`
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3. Validar metricas de modelos
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4. Generar reporte de entrenamiento
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### Fase 5: Documentacion
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1. Actualizar DATABASE_INVENTORY.yml
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2. Actualizar ML_INVENTORY.yml
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3. Crear carpeta TASK con CAPVED
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---
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## 2. Estimacion de Entregables
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| Entregable | Complejidad | Archivos |
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|------------|-------------|----------|
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| fetch_polygon_data.py | MEDIA | 1 |
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| database.py | ALTA | 1 |
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| Config files | BAJA | 3 |
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| 12 modelos | ALTA | 36 |
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| Documentacion | MEDIA | 4 |
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---
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## 3. Orden de Ejecucion
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```
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[1] Ambiente Python → [2] Datos → [3] Migration → [4] Training → [5] Docs
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↓ ↓ ↓ ↓ ↓
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venv OK 469K bars database.py 12 modelos TASK folder
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```
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