skip to content
Metric learning Preview this item
ClosePreview this item
Checking...

Metric learning

Author: Rahul Chandnani
Publisher: [Place of publication not identified] : [Technics Publications], [2017]
Edition/Format:   eVideo : Clipart/images/graphics : English
Summary:
"This video explores metric learning. These are the topics that will be covered: Intuition behind metric learning; Importance of metrics in various tasks of machine learning like classification and regression; Example of using information retrieval (image search); Mathematical definition of metric, commonly used metrics, and the process to choose a good metric according to the task at hand; Limitation of standard  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

Find a copy online

Links to this item

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Material Type: Clipart/images/graphics, Internet resource, Videorecording
Document Type: Internet Resource, Computer File, Visual material
All Authors / Contributors: Rahul Chandnani
OCLC Number: 1012108971
Notes: Title from title screen (viewed November 16, 2017).
Performer(s): Presenter, Rahul Chandnani.
Description: 1 online resource (1 streaming video file (1 hr., 5 min., 18 sec.)) : digital, sound, color
Responsibility: by Rahul Chandnani.

Abstract:

"This video explores metric learning. These are the topics that will be covered: Intuition behind metric learning; Importance of metrics in various tasks of machine learning like classification and regression; Example of using information retrieval (image search); Mathematical definition of metric, commonly used metrics, and the process to choose a good metric according to the task at hand; Limitation of standard metrics from a classification point of view; Formal definition of metric learning; Classification constraints on metric learning; Learn-able metrics (mahalanobis distance); Limitation of standard mahalanobis distance; How to modify mahalanobis distance to overcome limitations of using co-variance matrix; Science behind feature space transformation; Metric Learning Algorithms (LMNN and ITML); Algorithms as optimization problems; Limitations of linear metric learning and their solutions; How to do metric learning from a practical point of view using KNN; Pointers on approaching any problem using KNN and metric learning."--Resource description page.

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.

Similar Items

Related Subjects:(1)

Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


Primary Entity

<http://www.worldcat.org/oclc/1012108971> # Metric learning
    a schema:VideoObject, schema:Movie, schema:CreativeWork ;
    library:oclcnum "1012108971" ;
    rdfs:comment "Unknown 'gen' value: cig" ;
    schema:about <http://experiment.worldcat.org/entity/work/data/4616454943#Topic/machine_learning> ; # Machine learning
    schema:creator <http://experiment.worldcat.org/entity/work/data/4616454943#Person/chandnani_rahul> ; # Rahul Chandnani
    schema:datePublished "2017" ;
    schema:description ""This video explores metric learning. These are the topics that will be covered: Intuition behind metric learning; Importance of metrics in various tasks of machine learning like classification and regression; Example of using information retrieval (image search); Mathematical definition of metric, commonly used metrics, and the process to choose a good metric according to the task at hand; Limitation of standard metrics from a classification point of view; Formal definition of metric learning; Classification constraints on metric learning; Learn-able metrics (mahalanobis distance); Limitation of standard mahalanobis distance; How to modify mahalanobis distance to overcome limitations of using co-variance matrix; Science behind feature space transformation; Metric Learning Algorithms (LMNN and ITML); Algorithms as optimization problems; Limitations of linear metric learning and their solutions; How to do metric learning from a practical point of view using KNN; Pointers on approaching any problem using KNN and metric learning."--Resource description page."@en ;
    schema:exampleOfWork <http://worldcat.org/entity/work/id/4616454943> ;
    schema:inLanguage "en" ;
    schema:name "Metric learning"@en ;
    schema:productID "1012108971" ;
    schema:url <http://proquest.safaribooksonline.com/?fpi=9781634622882> ;
    schema:url <http://ezproxy.torontopubliclibrary.ca/login?url=http://proquestcombo.safaribooksonline.com/?uiCode=torontopl&xmlId=9781634622882> ;
    wdrs:describedby <http://www.worldcat.org/title/-/oclc/1012108971> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/4616454943#Person/chandnani_rahul> # Rahul Chandnani
    a schema:Person ;
    schema:familyName "Chandnani" ;
    schema:givenName "Rahul" ;
    schema:name "Rahul Chandnani" ;
    .


Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.