The document discusses a presentation about predicting Supreme Court decisions using machine learning models. A linear SVM classifier was trained and tested on past Supreme Court case data, achieving 70% prediction accuracy and an AUC of 0.696. The presentation also showed trends in Supreme Court decisions from 2006 to 2014 and important features for prediction like amicus briefs, words used, and sentiment of individual justices. It concludes with discussing a specific 2014 case called POM Wonderful v. Coca-Cola.
