Statistical Machine Learning | Larry Wasserman, CMU

Comprehensive course in statistical machine learning, including linear regression, classification, nonparametric methods, and more. Taught by renowned instructors Larry Wasserman and Ryan Tibshirani.

Introduction

This course covers a broad range of topics in statistical machine learning, including linear regression, linear classification, nonparametric regression, nonparametric classification, reproducing kernel Hilbert spaces, density estimation, and clustering. The course is taught by renowned instructors Larry Wasserman and Ryan Tibshirani, and features a comprehensive syllabus and video lectures.

Highlights

• Broad coverage of fundamental topics in statistical machine learning
• Taught by renowned instructors Larry Wasserman and Ryan Tibshirani
• Comprehensive syllabus with video lectures available
• Hands-on assignments and a project to apply the concepts learned

Recommendation

This course is highly recommended for students interested in machine learning, statistics, and data science. It provides a solid foundation in the theoretical and practical aspects of statistical machine learning, and is suitable for both beginners and experienced learners.