Machine Learning model(specifically log-regression with stochastic gradient descent) for tennis matches prediction. Achieves accuracy of 66% on approx. 125000 matches
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Updated
Feb 18, 2022 - Python
Machine Learning model(specifically log-regression with stochastic gradient descent) for tennis matches prediction. Achieves accuracy of 66% on approx. 125000 matches
An advanced machine learning model utilizes a Random Forest Regressor to generate betting recommendations for Major League Baseball (MLB) games.
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凯利标准计数|机数造物。
Tools to scrape data from the riot API and calculate stats used for eSports betting, such as first blood %
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finding patterns in up down sequences
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Data-driven, sports wagering model for MMA (mixed-martial-arts) contests.
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Machine Learning Model using NN, Xgboost To Get the Best Odds of NBA Game!
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