Provides a comprehensive theoretical grounding in machine learning.
Explores a wide range of machine learning algorithms and their applications.
Covers key concepts such as generalization, overfitting, and computational complexity.
Includes numerous case studies and examples to illustrate key ideas.
* Suitable for advanced undergraduate and graduate students in computer science and related fields.