This project predicts horse racing outcomes using machine learning models trained on historical race and horse data from 1990-2020. It explores feature engineering, odds analysis, and performance metrics to tackle the sport's complexity and improve predictive accuracy across diverse racing conditions.
python data-science machine-learning numpy scikit-learn regression prediction pandas seaborn classification matplotlib horse-racing feature-engineering historical-data model-evaluation sports-data betting-odds sports-analytics ai-prediction racing-performance
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Updated
Jan 26, 2026 - Jupyter Notebook