Marko Djordjevic fd29ab91e0 feat(ml): implement feature engineering pipeline ... - Create pipeline.py with CLI argument parsing for running stages - Implement TA-Lib indicator computation with multi-output support - Add candle feature extraction (body_size, wicks, ratios, etc.) - Create custom feature loader with dynamic module import - Wire all feature engineering stages with NaN handling - Tasks completed: 2.2, 2.3, 3.1, 3.2, 3.3, 3.4, 3.5		2026-02-15 12:22:59 +01:00
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.dvc	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
app	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
candle_ml.egg-info	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
config	feat: add ML service scaffolding with Python FastAPI, Docker, and MLflow setup	2026-02-15 11:58:31 +01:00
features	feat(ml): implement feature engineering pipeline	2026-02-15 12:22:59 +01:00
migrations	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
.dvcignore	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00
Dockerfile	feat: add ML service scaffolding with Python FastAPI, Docker, and MLflow setup	2026-02-15 11:58:31 +01:00
pipeline.py	feat(ml): implement feature engineering pipeline	2026-02-15 12:22:59 +01:00
pyproject.toml	feat(ml): add database schema, config parser, and DVC setup	2026-02-15 12:08:53 +01:00