An Introduction to Optimization: With Applications to Machine Learning 5th Edition

An Introduction to Optimization: With Applications to Machine Learning (5th Edition)

Authors: Edwin K. P. Chong, Wu-Sheng Lu, Stanislaw H. Zak
Edition: 5th Edition
Binding: Paperback / Hardcover
Language: English
Category: Optimization / Machine Learning / Mathematics / Engineering

An Introduction to Optimization: With Applications to Machine Learning (5th Edition) offers an in-depth introduction to the mathematical field of optimization, with an emphasis on its applications in machine learning. The textbook is designed for both students and professionals in computer science, engineering, and applied mathematics. It provides a clear understanding of optimization techniques and their practical applications in machine learning models.

The 5th edition includes updated content, new problems, and additional examples relevant to modern optimization in machine learning. The authors provide readers with theoretical concepts as well as practical tools for solving real-world optimization problems using algorithms and computational methods. Key optimization techniques such as convex optimization, gradient descent, and linear programming are explored in detail with clear explanations.

This edition also places special emphasis on applications in machine learning, discussing how optimization plays a crucial role in training models, improving performance, and solving complex machine learning tasks.

🔑 Key Features:

• Comprehensive coverage of optimization techniques and algorithms, with a focus on applications to machine learning

• Detailed explanations of convex optimization, gradient methods, linear and nonlinear programming, and more

• Numerous examples and exercises that demonstrate the application of optimization methods in real-world problems

• In-depth discussions on optimization algorithms used in machine learning, including their convergence properties and computational complexity

• Applications in machine learning: training algorithms, deep learning, support vector machines, and more

• Updated with new problems, examples, and MATLAB code to aid practical understanding

• Strong emphasis on both theoretical foundations and practical problem-solving techniques