Ruye Wang

Introduction to Machine Learning

From Math to Code

• Gebundenes Buch

Produktbeschreibung

Explore how and why machine learning algorithms work with this self-contained, hands-on textbook for senior undergraduate and graduate students. Using Matlab and Python, it includes over 85 worked examples demonstrating how to implement algorithms, and over 75 end-of-chapter problems empowering students to develop their own code.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 668
• Erscheinungstermin: 31. Juli 2025
• Englisch
• ISBN-13: 9781316519509
• ISBN-10: 1316519503
• Artikelnr.: 73535549

Autorenporträt

Ruye Wang is an Emeritus Professor of Engineering at Harvey Mudd College, with over thirty years of experience in teaching courses in Engineering and Computer Science. Previously a Principal Investigator at the Jet Propulsion Laboratory, NASA, his research interests include image processing, computer vision, machine learning and remote sensing. He is the author of the textbook Introduction to Orthogonal Transforms (2012).

Inhaltsangabe

Part I. Mathematical Foundations: 1. Solving Equations
2. Unconstrained Optimization
3. Constrained Optimization
Part II. Regression: 4. Bias-Variance Tradeoff and Overfitting vs Underfitting
5. Linear Regression
6. Nonlinear Regression
7. Logistic and Softmax Regression
8. Gaussian Process Regression and Classification
Part III. Feature Extraction: 9. Feature Selection
10. Principal Component Analysis
11. Variations of PCA
12. Independent Component Analysis
Part IV. Classification: 13. Statistic Classification
14. Support Vector machine
15. Clustering Analysis
16. Hierarchical Classifiers
17. Biologically Inspired Networks
18. Perceptron-Based Networks
19. Competition-Based Networks
Part VI. Reinforcement Learning: 20. Introduction to Reinforcement Learning.