A Course in Machine Learning
by Hal Daumé III
Publisher: ciml.info 2012
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.
Download or read it online for free here:
Download link
(2.9MB, PDF)
Similar books
Machine Learning for Designers
by Patrick Hebron - 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.
(6735 views)
by Patrick Hebron - 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.
(6735 views)
Information Theory, Inference, and Learning Algorithms
by David J. C. MacKay - Cambridge University Press
A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.
(28760 views)
by David J. C. MacKay - Cambridge University Press
A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.
(28760 views)
Learning Deep Architectures for AI
by Yoshua Bengio - Now Publishers
This book discusses the principles of learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models.
(7798 views)
by Yoshua Bengio - Now Publishers
This book discusses the principles of learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models.
(7798 views)
Foundations of Machine Learning
by M. Mohri, A. Rostamizadeh, A. Talwalkar - The MIT Press
This is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools.
(6204 views)
by M. Mohri, A. Rostamizadeh, A. Talwalkar - The MIT Press
This is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools.
(6204 views)