LEADER 03450nam 2200481 450 001 9910427686703321 005 20210211234015.0 010 $a3-030-36375-9 024 7 $a10.1007/978-3-030-36375-8 035 $a(CKB)4100000011445386 035 $a(DE-He213)978-3-030-36375-8 035 $a(MiAaPQ)EBC6348885 035 $a(PPN)250222558 035 $a(EXLCZ)994100000011445386 100 $a20210211d2020 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplying data science $ehow to create value with artificial intelligence /$fArthur K. Kordon 205 $a1st ed. 2020. 210 1$aCham, Switzerland :$cSpringer,$d[2020] 210 4$dİ2020 215 $a1 online resource (XXXII, 494 p. 262 illus., 195 illus. in color.) 311 $a3-030-36374-0 327 $aPart 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. 330 $aThis 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. 606 $aArtificial intelligence 606 $aBusiness$xData processing 606 $aBig data 615 0$aArtificial intelligence. 615 0$aBusiness$xData processing. 615 0$aBig data. 676 $a658.0563 700 $aKordon$b Arthur K.$0994821 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910427686703321 996 $aApplying data science$92278658 997 $aUNINA