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Deep ensemble EPL match prediction engine — 13 base learners, Dixon-Coles statistical model, 376+ engineered features, 8 data sources, NLP sentiment analysis. 60.2% accuracy, outperforms market odds.
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Extend .gitignore with test and type-checking cache patterns
03bd211View on GitHubAdd return type annotations to run_pipeline.py metric functions
be0252bView on GitHubAdd return type annotations to predict.py public functions
eb79db5View on GitHubAdd package-level docstrings to data, features, and models modules
9723874View on GitHubAdd professional repository infrastructure and enhance README with ensemble architecture details, walk-forward results, and confidence tier breakdowns
2ef2630View on GitHubUpdate README with latest pipeline results and dashboard serve docs
efadd9aView on GitHub8
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