*Take $10 off when you spend $50+! Use code NEWYEAR10. Ends Mon 5 Jan. T&Cs apply.
Track My Order
Help Centre
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore
Get Free Shipping on orders over $79
What Every Engineer Should Know About Data-Driven Analytics : What Every Engineer Should Know - Satish Mahadevan Srinivasan

What Every Engineer Should Know About Data-Driven Analytics

By: Satish Mahadevan Srinivasan, Phillip A. Laplante

eText | 13 April 2023 | Edition Number 1

At a Glance

eText

$104.50

or 4 interest-free payments of $26.13 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains.

  • Utilizes practical examples 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, self-assessments, and worked-out practice exercises.

Written to be accessible to non-experts in the subject, this comprehensive introductory text is suitable for students, professionals, and researchers in engineering and data science.

on
Desktop
Tablet
Mobile

You Can Find This eBook In

Non-FictionComputing & I.T.Computer Programming & Software DevelopmentSoftware EngineeringComputer ScienceSystems Analysis & DesignArtificial IntelligenceMachine LearningEngineering & TechnologyMechanical Engineering & MaterialsMaterials ScienceInformation Technology General Issue
Environmental ScienceEnergy Technology & EngineeringElectrical EngineeringTechnology in GeneralEngineering in GeneralElectronics & Communications EngineeringElectronics EngineeringAutomatic Control EngineeringMathematicsAlgorithms & Data Structures

Other Editions and Formats

Hardcover

Published: 13th April 2023

View Product

More in Machine Learning

HBR Guide to Generative AI for Managers : HBR Guide - Elisa Farri

eBOOK

HBR Guide to Generative AI for Managers

HBR Guide

eBook

RRP $37.26

$29.99

20%
OFF
Transformers in Action - Nicole Koenigstein

eBOOK

Transformers in Action

eBook

$44.99

Hugging Face in Action - Wei-Meng Lee

eBOOK

Hugging Face in Action

eBook

$37.99

Investing for Programmers - Stefan Papp

eBOOK

Investing for Programmers

eBook

$44.99

Deep Learning Crash Course - Giovanni Volpe

eBOOK

Deep Learning Crash Course

eBook

RRP $81.32

$65.99

19%
OFF
Causal AI - Robert Osazuwa Ness

eBOOK

Causal AI

eBook

$44.99

This product is categorised by