INFINITESKILLS_DEPENDENCY_GRAMMAR_AND_TAGGING_WITH_SPACY_TUTORIAL-OXBRiDGE

Section
Appz
Group
OXBRiDGE
Size
77,22 MB
Files
4
Date
2017-05-25

NFO

                                           
░ ░▒▒▒▓▓█████▌░░ University of OXford & University of camBRiDGE ░░▐████▓▓▒▒▒░ ░
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  ...is a collective term for characteristics that the two institutions share.


     ·-- PUBLISHER -----·> Infinite Skills                                    
     ·-- LECTURESHIP ---·> Dependency Grammar and Tagging with SpaCy          
                                                                              
                                                                              

     ·-- LECTURE DATE --·> 05-2017           
                           03-2017 {Published}
    
     ·-- PERIOD in HRS--·> 00+                                 
     ·-- SCALE ---------·> 02x50mb                                           

     ·-- LECTURE LINK --·> https://goo.gl/3nLG7v                     
                                                                                              
 
     
     Dependency grammar is a powerful way to represent syntactic             
     relationships within a sentence. More sophisticated than bag-of-words   
     representations, it's used in natural language processing tasks like    
     feature engineering, opinion mining, information retrieval, and relation
     extraction. In this course, which is designed for basic to intermediate 
     level Python programmers, you'll learn how to represent dependency      
     grammar as an extension to valency grammar and use it with spaCy.       
                                                                             
     Discover valency grammar and how it's used to express word relationships
     Understand dependency grammar as a typed extension to valency grammar   
     Explore the expressivity, assumptions, and limitations of dependency    
     grammar                                                                 
     Learn how to traverse parses with spaCy for various applications        
     Gain experience training a spaCy parser on a Twitter dataset            
     

Files

PathSize
ox_idgatwst.r0029,53 MB
ox_idgatwst.rar47,68 MB
ox_idgatwst.sfv52 B
oxbridge.nfo2,52 KB