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
到查詢結果
[ subject:"Machine learning." ]
切換:
標籤
|
MARC模式
|
ISBD
Personalized machine learning
~
McAuley, Julian.
FindBook
Google Book
Amazon
博客來
Personalized machine learning
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Personalized machine learning/ Julian McAuley.
作者:
McAuley, Julian.
出版者:
Cambridge, United Kingdom ; New York, NY :Cambridge University Press, : 2022.,
面頁冊數:
x, 326 p. :ill., digital ;23 cm.
附註:
Title from publisher's bibliographic system (viewed on 24 Jan 2022).
標題:
Machine learning. -
電子資源:
https://doi.org/10.1017/9781009003971
ISBN:
9781009003971
Personalized machine learning
McAuley, Julian.
Personalized machine learning
[electronic resource] /Julian McAuley. - Cambridge, United Kingdom ; New York, NY :Cambridge University Press,2022. - x, 326 p. :ill., digital ;23 cm.
Title from publisher's bibliographic system (viewed on 24 Jan 2022).
Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.
ISBN: 9781009003971Subjects--Topical Terms:
533906
Machine learning.
LC Class. No.: Q325.5 / .M386 2022
Dewey Class. No.: 006.31
Personalized machine learning
LDR
:01856nmm a2200241 a 4500
001
2324534
003
UkCbUP
005
20220204062405.0
006
m d
007
cr nn 008maaau
008
231215s2022 enk o 1 0 eng d
020
$a
9781009003971
$q
(electronic bk.)
020
$a
9781316518908
$q
(hardback)
035
$a
CR9781009003971
040
$a
UkCbUP
$b
eng
$c
UkCbUP
$d
GP
050
0 0
$a
Q325.5
$b
.M386 2022
082
0 4
$a
006.31
$2
23
090
$a
Q325.5
$b
.M117 2022
100
1
$a
McAuley, Julian.
$3
3645852
245
1 0
$a
Personalized machine learning
$h
[electronic resource] /
$c
Julian McAuley.
260
$a
Cambridge, United Kingdom ; New York, NY :
$b
Cambridge University Press,
$c
2022.
300
$a
x, 326 p. :
$b
ill., digital ;
$c
23 cm.
500
$a
Title from publisher's bibliographic system (viewed on 24 Jan 2022).
520
$a
Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.
650
0
$a
Machine learning.
$3
533906
856
4 0
$u
https://doi.org/10.1017/9781009003971
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
W9456481
電子資源
11.線上閱覽_V
電子書
EB Q325.5 .M386 2022
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