An Introduction to Optimization: With Applications to Machine Learning 4th Edition by Edwin K. P. Chong
- Publisher: MATHEMATICS
- Availability: In Stock
- SKU: 26393
- Number of Pages: 622
Rs.1,230.00
Rs.1,695.00
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An Introduction to Optimization: With Applications to Machine Learning (4th Edition)
Author: Edwin K. P. Chong
Binding: Paperback
Paper Quality: Yellow Paper
Category: Mathematics, Optimization, Machine Learning
Recommended For:
BS/MS students in Computer Science, Engineering, Mathematics, and Data Science; also ideal for machine learning enthusiasts and researchers in optimization.
Key Points:
-
Foundations of Optimization Theory
Covers both linear and nonlinear optimization, constrained and unconstrained problems, providing a strong mathematical base. -
Machine Learning Applications
Updated to include real-world ML use cases, such as gradient descent, Lagrangian methods, and stochastic optimization, relevant to modern AI systems. -
Algorithmic Approach
Focuses on practical algorithms with step-by-step derivations, including Newton’s method, simplex method, and KKT conditions. -
Exercises and MATLAB Examples
Includes MATLAB code snippets and exercises to help students simulate and visualize optimization problems. -
Well-Structured for Learning
Designed to suit both classroom instruction and self-paced study with clear explanations and problem sets.
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Writer ✤ Edwin K. P. Chong (Author),
Stanislaw H. Zak (Author)
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