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Predict Player Efficiency with Random Forest
I'm looking for a data analyst with experience in machine learning and regression analysis, specifically using Random Forest, to predict player performance, specifically the Player Efficiency Rating (PER). Data Type: - Game statistics: We have comprehensive records of players' game performances. - Biometric data: This includes physical measurements and health indicators, relevant to performance prediction. Data Frequency: - Our data is updated daily, providing a dynamic and current dataset for analysis. The ideal candidate should: - Have a strong background in data science and machine learning - Be proficient in using Random Forest for regression analysis - Have experience working with sports data - Be able to deliver insightful predictions on player efficiency This project ...