Unsupervised Learning

Unsupervised Learning
Author :
Publisher : MIT Press
Total Pages : 420
Release :
ISBN-13 : 026258168X
ISBN-10 : 9780262581684
Rating : 4/5 (84 Downloads)

Book Synopsis Unsupervised Learning by : Geoffrey Hinton

Download or read book Unsupervised Learning written by Geoffrey Hinton and published by MIT Press. This book was released on 1999-05-24 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.


Unsupervised Learning Related Books

Unsupervised Learning
Language: en
Pages: 420
Authors: Geoffrey Hinton
Categories: Medical
Type: BOOK - Published: 1999-05-24 - Publisher: MIT Press

DOWNLOAD EBOOK

Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by
Hands-On Unsupervised Learning Using Python
Language: en
Pages: 310
Authors: Ankur A. Patel
Categories: Computers
Type: BOOK - Published: 2019-02-21 - Publisher: "O'Reilly Media, Inc."

DOWNLOAD EBOOK

Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence.
Unsupervised Learning Algorithms
Language: en
Pages: 564
Authors: M. Emre Celebi
Categories: Technology & Engineering
Type: BOOK - Published: 2016-04-29 - Publisher: Springer

DOWNLOAD EBOOK

This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, un
Machine Learning Foundations
Language: en
Pages: 391
Authors: Taeho Jo
Categories: Technology & Engineering
Type: BOOK - Published: 2021-02-12 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists
Interpretable Machine Learning
Language: en
Pages: 320
Authors: Christoph Molnar
Categories: Computers
Type: BOOK - Published: 2020 - Publisher: Lulu.com

DOWNLOAD EBOOK

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simp