語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Applying Data Science = How to Creat...
~
SpringerLink (Online service)
Applying Data Science = How to Create Value with Artificial Intelligence /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Applying Data Science/ by Arthur K. Kordon.
其他題名:
How to Create Value with Artificial Intelligence /
作者:
Kordon, Arthur K.
面頁冊數:
XXXII, 494 p. 262 illus., 195 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Computational Intelligence. -
電子資源:
https://doi.org/10.1007/978-3-030-36375-8
ISBN:
9783030363758
Applying Data Science = How to Create Value with Artificial Intelligence /
Kordon, Arthur K.
Applying Data Science
How to Create Value with Artificial Intelligence /[electronic resource] :by Arthur K. Kordon. - 1st ed. 2020. - XXXII, 494 p. 262 illus., 195 illus. in color.online resource.
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.
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.
ISBN: 9783030363758
Standard No.: 10.1007/978-3-030-36375-8doiSubjects--Topical Terms:
768837
Computational Intelligence.
LC Class. No.: Q334-342
Dewey Class. No.: 006.3
Applying Data Science = How to Create Value with Artificial Intelligence /
LDR
:03434nam a22003975i 4500
001
1028853
003
DE-He213
005
20200912154904.0
007
cr nn 008mamaa
008
210318s2020 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
035
$a
978-3-030-36375-8
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
$3
1325445
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
2 4
$a
Computational Intelligence.
$3
768837
650
2 4
$a
Big Data.
$3
1017136
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
677765
650
2 4
$a
Big Data/Analytics.
$3
1106909
650
1 4
$a
Artificial Intelligence.
$3
646849
650
0
$a
Computational intelligence.
$3
568984
650
0
$a
Data mining.
$3
528622
650
0
$a
Big data.
$3
981821
650
0
$a
Artificial intelligence.
$3
559380
710
2
$a
SpringerLink (Online service)
$3
593884
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)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入