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Information Geometry & Applications | UCSD MATH 273B | Melvin Leok

UCSD

Explore the mathematical foundations of information theory, machine learning, and optimization with UCSD's MATH 273B course on Information Geometry and its Applications.

University CoursesMachine Learning

Introduction

This course explores the field of information geometry and its various applications. Information geometry is a branch of mathematics that studies the geometric structure of statistical manifolds, which are spaces of probability distributions.

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Highlights

  • Covers the fundamental concepts and techniques of information geometry
  • Examines the applications of information geometry in areas such as machine learning, signal processing, and optimization
  • Taught by Melvin Leok, a renowned expert in the field of information geometry

Recommendation

This course is recommended for students and researchers interested in the mathematical foundations of information theory, machine learning, and other related fields. It provides a deep dive into the theoretical and practical aspects of information geometry and its diverse applications.

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