Can I read Machine Learning : A Constraint-Based Approach on EtoBox?

Machine Learning : A Constraint-Based Approach by Marco Gori Ph.D is a nonfiction available to read on EtoBox.

What is Machine Learning : A Constraint-Based Approach about?

Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic knowledge bases as a collection of constraints, the book draws a path towards a deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, like in fuzzy systems. A special attention is reserved to deep learning, which nicely fits the constrained- based approach followed in this book. This book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, and includes many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included. Presents fundamental machine learning concepts, such as neural networks and kernel machines in a unified man

Who reads Machine Learning : A Constraint-Based Approach?

Author

Marco Gori Ph.D

Publisher

Elsevier Science

Published

2017

Language

EN

ISBN

9780081006597

Category

nonfiction

Subjects

Computer Science, Mathematics, Science