語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Artificial intelligence, big data an...
~
Steland, Ansgar.
FindBook
Google Book
Amazon
博客來
Artificial intelligence, big data and data science in statistics = challenges and solutions in environmetrics, the natural sciences and technology /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Artificial intelligence, big data and data science in statistics/ edited by Ansgar Steland, Kwok-Leung Tsui.
其他題名:
challenges and solutions in environmetrics, the natural sciences and technology /
其他作者:
Steland, Ansgar.
出版者:
Cham :Springer International Publishing : : 2022.,
面頁冊數:
viii, 376 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Artificial intelligence. -
電子資源:
https://doi.org/10.1007/978-3-031-07155-3
ISBN:
9783031071553
Artificial intelligence, big data and data science in statistics = challenges and solutions in environmetrics, the natural sciences and technology /
Artificial intelligence, big data and data science in statistics
challenges and solutions in environmetrics, the natural sciences and technology /[electronic resource] :edited by Ansgar Steland, Kwok-Leung Tsui. - Cham :Springer International Publishing :2022. - viii, 376 p. :ill., digital ;24 cm.
This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book's expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.
ISBN: 9783031071553
Standard No.: 10.1007/978-3-031-07155-3doiSubjects--Topical Terms:
516317
Artificial intelligence.
LC Class. No.: Q335
Dewey Class. No.: 006.3
Artificial intelligence, big data and data science in statistics = challenges and solutions in environmetrics, the natural sciences and technology /
LDR
:02165nmm a2200313 a 4500
001
2305793
003
DE-He213
005
20221115005420.0
006
m d
007
cr nn 008maaau
008
230409s2022 sz s 0 eng d
020
$a
9783031071553
$q
(electronic bk.)
020
$a
9783031071546
$q
(paper)
024
7
$a
10.1007/978-3-031-07155-3
$2
doi
035
$a
978-3-031-07155-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
Q335
072
7
$a
PBT
$2
bicssc
072
7
$a
MAT029000
$2
bisacsh
072
7
$a
PBT
$2
thema
082
0 4
$a
006.3
$2
23
090
$a
Q335
$b
.A791 2022
245
0 0
$a
Artificial intelligence, big data and data science in statistics
$h
[electronic resource] :
$b
challenges and solutions in environmetrics, the natural sciences and technology /
$c
edited by Ansgar Steland, Kwok-Leung Tsui.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2022.
300
$a
viii, 376 p. :
$b
ill., digital ;
$c
24 cm.
520
$a
This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book's expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.
650
0
$a
Artificial intelligence.
$3
516317
650
0
$a
Mathematical statistics
$x
Data processing.
$3
532521
650
0
$a
Big data.
$3
2045508
700
1
$a
Steland, Ansgar.
$3
2134859
700
1
$a
Tsui, Kwok-Leung.
$3
3609229
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
856
4 0
$u
https://doi.org/10.1007/978-3-031-07155-3
950
$a
Mathematics and Statistics (SpringerNature-11649)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9447342
電子資源
11.線上閱覽_V
電子書
EB Q335
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入