Reverse Hypothesis Machine Learning - A Practitioner's Perspective (Paperback, Softcover reprint of the original 1st ed. 2017)

This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same-the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as well as machine intelligence enthusiasts. It can also used by practitioners to develop new machine learning applications to solve problems that require creativity.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Intelligent Systems Reference Library, 128
Release date:	July 2018
First published:	2017
Authors:	Parag Kulkarni
Dimensions:	235 x 155 x 8mm (L x W x T)
Format:	Paperback
Pages:	138
Edition:	Softcover reprint of the original 1st ed. 2017
ISBN-13:	978-3-319-85626-1
Categories:	Books > Business & Economics > Business & management > Management of specific areas > Research & development management Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Mechanical engineering & materials > Mechanical engineering > Engines & power transmission > General Promotions
LSN:	3-319-85626-X
Barcode:	9783319856261

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