語系:
繁體中文
English
日文
簡体中文
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Predictive analytics with Microsoft ...
~
Barga, Roger.
Predictive analytics with Microsoft Azure machine learning[electronic resource] /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
杜威分類號:
005.74
書名/作者:
Predictive analytics with Microsoft Azure machine learning/ by Roger Barga, Valentine Fontama, Wee Hyong Tok.
作者:
Barga, Roger.
其他作者:
Fontama, Valentine.
出版者:
Berkeley, CA : : Apress :, 2015.
面頁冊數:
250 p. : : ill., digital ;; 24 cm.
Contained By:
Springer eBooks
標題:
Data Mining and Knowledge Discovery.
標題:
Information technology - Management.
標題:
Computer Science.
標題:
Computer Science, general.
ISBN:
9781484212004
ISBN:
9781484212011
摘要、提要註:
Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models. The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services. Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft. What's New in the Second Edition? Five new chapters have been added with practical detailed coverage of: Python Integration - a new feature announced February 2015 Data preparation and feature selection Data visualization with Power BI Recommendation engines Selling your models on Azure Marketplace.
電子資源:
http://dx.doi.org/10.1007/978-1-4842-1200-4
Predictive analytics with Microsoft Azure machine learning[electronic resource] /
Barga, Roger.
Predictive analytics with Microsoft Azure machine learning
[electronic resource] /by Roger Barga, Valentine Fontama, Wee Hyong Tok. - 2nd ed. - Berkeley, CA :Apress :2015. - 250 p. :ill., digital ;24 cm.
Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models. The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services. Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft. What's New in the Second Edition? Five new chapters have been added with practical detailed coverage of: Python Integration - a new feature announced February 2015 Data preparation and feature selection Data visualization with Power BI Recommendation engines Selling your models on Azure Marketplace.
ISBN: 9781484212004
Standard No.: 10.1007/978-1-4842-1200-4doiSubjects--Uniform Titles:
Windows Azure.
Subjects--Topical Terms:
464541
Data Mining and Knowledge Discovery.
LC Class. No.: HD30.2
Dewey Class. No.: 005.74
Predictive analytics with Microsoft Azure machine learning[electronic resource] /
LDR
:02192nam a2200313 a 4500
001
443609
003
DE-He213
005
20160302144544.0
006
m d
007
cr nn 008maaau
008
160715s2015 cau s 0 eng d
020
$a
9781484212004
$q
(electronic bk.)
020
$a
9781484212011
$q
(paper)
024
7
$a
10.1007/978-1-4842-1200-4
$2
doi
035
$a
978-1-4842-1200-4
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HD30.2
072
7
$a
UY
$2
bicssc
072
7
$a
COM014000
$2
bisacsh
082
0 4
$a
005.74
$2
23
090
$a
HD30.2
$b
.B251 2015
100
1
$a
Barga, Roger.
$3
634405
245
1 0
$a
Predictive analytics with Microsoft Azure machine learning
$h
[electronic resource] /
$c
by Roger Barga, Valentine Fontama, Wee Hyong Tok.
250
$a
2nd ed.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2015.
300
$a
250 p. :
$b
ill., digital ;
$c
24 cm.
520
$a
Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models. The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services. Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft. What's New in the Second Edition? Five new chapters have been added with practical detailed coverage of: Python Integration - a new feature announced February 2015 Data preparation and feature selection Data visualization with Power BI Recommendation engines Selling your models on Azure Marketplace.
630
0 0
$a
Windows Azure.
$3
634408
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
464541
650
0
$a
Information technology
$x
Management.
$3
337161
650
1 4
$a
Computer Science.
$3
423143
650
2 4
$a
Computer Science, general.
$3
463629
700
1
$a
Fontama, Valentine.
$3
634406
700
1
$a
Tok, Wee Hyong.
$3
634407
710
2
$a
SpringerLink (Online service)
$3
463450
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4842-1200-4
950
$a
Professional and Applied Computing (Springer-12059)
筆 0 讀者評論
多媒體
多媒體檔案
http://dx.doi.org/10.1007/978-1-4842-1200-4
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入