Logo

Understanding Machine Learning: From Theory to Algorithms

Large book cover: Understanding Machine Learning: From Theory to Algorithms

Understanding Machine Learning: From Theory to Algorithms
by

Publisher: Cambridge University Press
ISBN/ASIN: 1107057132
ISBN-13: 9781107057135
Number of pages: 449

Description:
The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.

Home page url

Download or read it online for free here:
Download link
(2.5MB, PDF)

Similar books

Book cover: Machine Learning for DesignersMachine Learning for Designers
by - O'Reilly Media
This book introduces you to contemporary machine learning systems and helps you integrate machine-learning capabilities into your user-facing designs. Patrick Hebron explains how machine-learning applications can affect the way you design websites.
(5349 views)
Book cover: A Course in Machine LearningA Course in Machine Learning
by - ciml.info
Tis is a set of introductory materials that covers most major aspects of modern machine learning (supervised and unsupervised learning, large margin methods, probabilistic modeling, etc.). It's focus is on broad applications with a rigorous backbone.
(19156 views)
Book cover: Machine Learning for Data StreamsMachine Learning for Data Streams
by - The MIT Press
This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA, allowing readers to try out the techniques after reading the explanations.
(4996 views)
Book cover: Practical Artificial Intelligence Programming in JavaPractical Artificial Intelligence Programming in Java
by - Lulu.com
The book uses the author's libraries and the best of open source software to introduce AI (Artificial Intelligence) technologies like neural networks, genetic algorithms, expert systems, machine learning, and NLP (natural language processing).
(22619 views)