What Every Engineer Should Know About Data-Driven Analytics (Hardcover)

• Utilizes case studies from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making • Introduces various approaches to build models that exploits different algorithms • Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets • Explores the augmentation of technical and mathematical materials with explanatory worked examples • Includes a glossary, lecture notes, self-assessments, and worked-out practice exercises

General

Imprint:	Taylor & Francis
Country of origin:	United Kingdom
Series:	What Every Engineer Should Know
Release date:	April 2023
First published:	2023
Authors:	Satish Mahadevan Srinivasan • Phillip A Laplante
Dimensions:	234 x 156mm (L x W)
Format:	Hardcover
Pages:	260
ISBN-13:	978-1-03-223543-1
Categories:	Books > Computing & IT > General Books > Science & Mathematics > Mathematics > General Books > Professional & Technical > Technology: general issues > Engineering: general Books > Professional & Technical > Environmental engineering & technology > General Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN:	1-03-223543-8
Barcode:	9781032235431

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