{"data":{"full_name":"fischlerben/NBA-Position-Predictor","name":"NBA-Position-Predictor","description":"Machine Learning project using 15 seasons of NBA data (2005-2020) to predict player position.  Decision Trees, Random Forests, Support Vector Machines (SVMs) and Gradient Boosted Trees (GBTs) utilized.  Example PCA transformation of X-data included as well.  Specific predictions made at the end, leading to interesting insights into what players are out-of-position.","stars":9.0,"forks":2.0,"language":"Jupyter Notebook","license":null,"archived":0.0,"subcategory":"nba-game-prediction","last_pushed_at":"2021-02-09T02:18:24+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":0.0,"adoption_score":5.0,"maturity_score":8.0,"community_score":13.0,"quality_score":26.0,"quality_tier":"experimental","risk_flags":"['no_license', 'stale_6m', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-12T10:12:43.919359+00:00"}}