Learning methods for applications. Content may include data preparation, regression and classification algorithms, support vector machines, random forests, class imbalance, overfitting, decision theory, recommender systems and collaborative filtering, text mining, analyzing social networks and social media, protecting privacy, A/B testing. CSE 103 or similar recommended.
Prerequisites:
graduate standing in CSE or consent of instructor.
New Spring 2013