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Optimization | Machine Learning | CMU 10-725 Fall 2012

Carnegie-Mellon University

Comprehensive optimization course covering first-order methods, Newton's method, duality, and advanced topics. Taught by experienced instructors at Carnegie Mellon University.

University CoursesMachine Learning

Introduction

10-725 Optimization Fall 2012 is a course offered at the School of Computer Science, Carnegie Mellon University. The course covers various optimization techniques and methods, including first-order methods, Newton's method, duality, and advanced topics.

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Highlights

  • Covers a wide range of optimization topics, from basic gradient descent to advanced techniques
  • Taught by experienced instructors Geoff Gordon and Ryan Tibshirani
  • Includes lecture videos, slides, and scribed notes for each lecture
  • Opportunity to contribute as a scribe and participate in the course

Recommendation

This course is recommended for students and professionals interested in optimization, machine learning, and related fields. It provides a comprehensive understanding of optimization techniques and their applications, making it a valuable resource for those looking to enhance their optimization skills.

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