Large Scale Machine Learning | University of Toronto

Comprehensive graduate-level course covering advanced machine learning techniques, including Bayesian methods, graphical models, and sequential data modeling. Hands-on experience with real-world datasets and programming assignments.

Introduction

STA 4273H is a graduate-level course on large-scale machine learning, covering a wide range of topics including Bayesian methods, graphical models, variational inference, and sequential data modeling.

Highlights

• Comprehensive coverage of advanced machine learning techniques
• Hands-on experience with real-world datasets and programming assignments
• Video lectures and detailed lecture notes available online
• Opportunity for student presentations and discussions

Recommendation

This course is recommended for graduate students and researchers interested in machine learning, data science, and statistical modeling. It provides a solid foundation in both the theoretical and practical aspects of large-scale machine learning, making it a valuable resource for those looking to expand their knowledge and skills in this field.