Predict Baseball Stats using Machine Learning and Python

We'll predict future season stats for baseball players using machine learning. The stat we'll predict is the wins above replacement (WAR) a player will generate next season. We'll first download and clean baseball season data using python and pybaseball. We'll do feature selection using a sequential feature selector to identify the most promising predictors for machine learning. We'll then train a ridge regression model to predict future season WAR. We'll measure error and improve the model. In the end, you'll have a model that can predict future season WAR and the next steps to improve the model. You can find the full code here - [project-walkthroughs/baseball_games at master · dataquestio/project-walkthroughs · GitHub](https://github.com/dataquestio/project-walkthroughs/tree/master/baseball_games) Chapters 00:00 Introduction 02:00 - Download the data 05:52 - Creating an ML target 09:15 - Cleaning the data 16:19 - Selecting useful features 27:13 - Making predictions with ML 38:15 - Improving accuracy 49:26 - Diagnosing issues with the model 52:28 - Wrap-up and next steps with the model ----------------------------- Join 1M+ Dataquest learners today! Master data skills and change your life. Sign up for free: https://bit.ly/3O8MDef