Logo

A Course in Machine Learning

Small book cover: A Course in Machine Learning

A Course in Machine Learning
by

Publisher: ciml.info
Number of pages: 189

Description:
CIML is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.). It's focus is on broad applications with a rigorous backbone.

Home page url

Download or read it online for free here:
Download link
(2.9MB, PDF)

Similar books

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.
(6360 views)
Book cover: Gaussian Processes for Machine LearningGaussian Processes for Machine Learning
by - The MIT Press
Gaussian processes provide a principled, practical, probabilistic approach to learning in kernel machines. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics.
(27555 views)
Book cover: Boosting: Foundations and AlgorithmsBoosting: Foundations and Algorithms
by - The MIT Press
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate 'rules of thumb'. A remarkably rich theory has evolved around boosting, with connections to a range of topics.
(6426 views)
Book cover: Machine Learning: A Probabilistic PerspectiveMachine Learning: A Probabilistic Perspective
by - The MIT Press
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms.
(3612 views)