Applying Data Science How to Create Value with Artificial Intelligence /

This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: mach...

Full description

Main Author: Kordon, Arthur K. (Author, http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2020.
Edition:1st ed. 2020.
Subjects:
Online Access:https://doi.org/10.1007/978-3-030-36375-8
LEADER 04287nam a22005295i 4500
001 978-3-030-36375-8
003 DE-He213
005 20210621111830.0
007 cr nn 008mamaa
008 200912s2020 gw | s |||| 0|eng d
020 |a 9783030363758  |9 978-3-030-36375-8 
024 7 |a 10.1007/978-3-030-36375-8  |2 doi 
050 4 |a Q334-342 
072 7 |a UYQ  |2 bicssc 
072 7 |a COM004000  |2 bisacsh 
072 7 |a UYQ  |2 thema 
082 0 4 |a 006.3  |2 23 
100 1 |a Kordon, Arthur K.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Applying Data Science  |h [electronic resource] :  |b How to Create Value with Artificial Intelligence /  |c by Arthur K. Kordon. 
250 |a 1st ed. 2020. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2020. 
300 |a XXXII, 494 p. 262 illus., 195 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a Part I, From Business Problems to Data Science -- Data Science Based on Artificial Intelligence -- Business Problems Dependent on Data -- Artificial Intelligence-Based Data Science Solutions -- Integrate and Conquer -- The Lost-in-Translation Trap -- Part II, The AI-Based Data Science Toolbox -- The AI-Based Data Science Workflow -- Problem Knowledge Acquisition -- Data Preparation -- Data Analysis -- Model Development -- The Model Deployment Life Cycle -- Part III, AI-Based Data Science in Action -- Infrastructure -- People -- Applications of AI-Based Data Science in Manufacturing -- Applications of AI-Based Data Science in Business -- How to Operate AI-Based Data Science in a Business -- How to Become an Effective Data Scientist -- Glossary. 
520 |a This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: machine learning, deep learning, decision trees and random forests, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem knowledge acquisition, data preparation, data analysis, model development, and model deployment lifecycle. Finally, in Part III the author illustrates the power of AI-based data science with successful applications in manufacturing and business. He also shows how to introduce this technology in a business setting and guides the reader on how to build the appropriate infrastructure and develop the required skillsets. The book is ideal for data scientists who will implement the proposed methodology and techniques in their projects. It is also intended to help business leaders and entrepreneurs who want to create competitive advantage by using AI-based data science, as well as academics and students looking for an industrial view of this discipline. 
650 0 |a Artificial intelligence. 
650 0 |a Big data. 
650 0 |a Data mining. 
650 0 |a Computational intelligence. 
650 1 4 |a Artificial Intelligence.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000 
650 2 4 |a Big Data/Analytics.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/522070 
650 2 4 |a Data Mining and Knowledge Discovery.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I18030 
650 2 4 |a Big Data.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I29120 
650 2 4 |a Computational Intelligence.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/T11014 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783030363741 
776 0 8 |i Printed edition:  |z 9783030363765 
776 0 8 |i Printed edition:  |z 9783030363772 
856 4 0 |u https://doi.org/10.1007/978-3-030-36375-8 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710)