國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Predictive analytics with Microsoft Azure machine learningby 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:	Information technologyManagement.
電子資源:	http://dx.doi.org/10.1007/978-1-4842-1200-4
ISBN:	9781484212004$q(electronic bk.)

Predictive analytics with Microsoft Azure machine learning
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$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-1200-4doiSubjects--Uniform Titles:

Windows Azure.
Subjects--Topical Terms:

183357
Information technology
--Management.

LC Class. No.: HD30.2

Dewey Class. No.: 005.74

Predictive analytics with Microsoft Azure machine learning
LDR:02192nmm a2200313 a 4500 001 475219
003 DE-He213
005 20160302144544.0
006 m d
007 cr nn 008maaau
008 160420s2015 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 702969
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 541398
650 0 $a Information technology $x Management. $3 183357
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Computer Science, general. $3 274540
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
700 1 $a Fontama, Valentine. $3 702970
700 1 $a Tok, Wee Hyong. $3 702971
710 2 $a SpringerLink (Online service) $3 273601
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)