Machine Learning Refined: Foundations, Algorithms, and Applications
- Author: Jeremy Watt
- Edition: 2nd
- Publisher: Cambridge University Press
- Publication Date: March 12, 2020
- ISBN-10: 1108480721
- ISBN-13: 978-1108480727
With its intuitive yet rigorous approach to machine learning, this text provides the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, offering a fresh and accessible way to learn by including detailed coverage of all essential mathematical prerequisites.
Practical applications are a core focus, featuring examples from a wide array of disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. The content is designed to bridge the gap between theoretical foundations and real-world implementation.
Key features of this edition include:
- Visual Clarity: Over 300 meticulously designed color illustrations that enable an intuitive grasp of complex technical concepts.
- Practical Coding: Over 100 in-depth coding exercises in Python that provide a functional understanding of crucial machine learning algorithms.
- Comprehensive Scope: Detailed exploration of foundations, algorithms, and diverse applications suitable for graduate-level study and professional reference.
- Support Resources: Access to a suite of supplemental materials including sample code, data sets, and interactive lecture slides.
Mastering the intricacies of machine learning is made achievable through this volume, making it an ideal resource for both structured classroom environments and individual self-study.