Logo

Learning Deep Architectures for AI

Large book cover: Learning Deep Architectures for AI

Learning Deep Architectures for AI
by

Publisher: Now Publishers
ISBN/ASIN: 1601982941
ISBN-13: 9781601982940
Number of pages: 130

Description:
This monograph discusses the motivations and principles regarding 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 such as Deep Belief Networks.

Home page url

Download or read it online for free here:
Download link
(1.1MB, 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.
(2485 views)
Book cover: Foundations of Machine LearningFoundations of Machine Learning
by - 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.
(873 views)
Book cover: Lecture Notes in Machine LearningLecture Notes in Machine Learning
by - Central Connecticut State University
Contents: Introduction; Concept learning; Languages for learning; Version space learning; Induction of Decision trees; Covering strategies; Searching the generalization / specialization graph; Inductive Logic Progrogramming; Unsupervised Learning ...
(5376 views)
Book cover: Machine Learning, Neural and Statistical ClassificationMachine Learning, Neural and Statistical Classification
by - Ellis Horwood
The book provides a review of different approaches to classification, compares their performance on challenging data-sets, and draws conclusions on their applicability to realistic industrial problems. A wide variety of approaches has been taken.
(20702 views)