The Resource Learning vector space models with SpaCy : build dense vector representations of text, and train them using Gensim, with Aaron Kramer

Learning vector space models with SpaCy : build dense vector representations of text, and train them using Gensim, with Aaron Kramer

Label
Learning vector space models with SpaCy : build dense vector representations of text, and train them using Gensim
Title
Learning vector space models with SpaCy
Title remainder
build dense vector representations of text, and train them using Gensim
Statement of responsibility
with Aaron Kramer
Creator
Speaker
Subject
Language
eng
Summary
"Information representation is a fundamental aspect of computational linguistics and learning from unstructured data. This course explores vector space models, how they're used to represent the meaning of words and documents, and how to create them using Python-based spaCy. You'll learn about several types of vector space models, how they relate to each other, and how to determine which model is best for natural language processing applications like information retrieval, indexing, and relevancy rankings. The course begins with a look at various encodings of sparse document-term matrices, moves on to dense vector representations that need to be learned, touches on latent semantic analysis, and finishes with an exploration of representation learning from neural network models with a focus on word2vec and Gensim. To get the most out of this course, learners should have intermediate level Python skills."--Resource description page
Cataloging source
UMI
Characteristic
videorecording
http://library.link/vocab/creatorName
Kramer, Aaron
LC call number
QA76.9.N38
PerformerNote
Presenter, Aaron Kramer
Runtime
33
http://library.link/vocab/subjectName
  • Natural language processing (Computer science)
  • Python (Computer program language)
Technique
live action
Label
Learning vector space models with SpaCy : build dense vector representations of text, and train them using Gensim, with Aaron Kramer
Link
http://databases.mvlc.org/connect/safari?uiCode=&xmlId=9781491986042
Instantiates
Publication
Note
  • Title from title screen (viewed April 11, 2017)
  • Date of publication from resource description page
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Configuration of playback channels
unknown
Content category
two-dimensional moving image
Content type code
  • tdi
Content type MARC source
rdacontent
Control code
ocn982197782
Dimensions
unknown
Extent
1online resource (1 volume)
Form of item
online
Media category
  • computer
  • video
Media MARC source
  • rdamedia
  • rdamedia
Media type code
  • c
  • v
Medium for sound
other
Other physical details
illustrations.
Sound
sound
Sound on medium or separate
sound on medium
Specific material designation
  • remote
  • other
Stock number
CL0500000847
System control number
(OCoLC)982197782
Video recording format
other
Label
Learning vector space models with SpaCy : build dense vector representations of text, and train them using Gensim, with Aaron Kramer
Link
http://databases.mvlc.org/connect/safari?uiCode=&xmlId=9781491986042
Publication
Note
  • Title from title screen (viewed April 11, 2017)
  • Date of publication from resource description page
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Configuration of playback channels
unknown
Content category
two-dimensional moving image
Content type code
  • tdi
Content type MARC source
rdacontent
Control code
ocn982197782
Dimensions
unknown
Extent
1online resource (1 volume)
Form of item
online
Media category
  • computer
  • video
Media MARC source
  • rdamedia
  • rdamedia
Media type code
  • c
  • v
Medium for sound
other
Other physical details
illustrations.
Sound
sound
Sound on medium or separate
sound on medium
Specific material designation
  • remote
  • other
Stock number
CL0500000847
System control number
(OCoLC)982197782
Video recording format
other

Library Locations

    • Merrimack Valley Library ConsortiumBorrow it
      4 High Street, Suite 175, North Andover, MA, 01845, US
      42.7009413 -71.1255084
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