Natural Language Generation (INFOMNLG)

Universiteit Utrecht (UU)

Hier vind je de beste samenvattingen om te slagen voor Natural Language Generation (INFOMNLG). Er zijn o.a. samenvattingen, aantekeningen en oefenvragen beschikbaar.

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Cheat Sheet -  Natural Language Generation (INFOMNLG)
  • Cheat Sheet - Natural Language Generation (INFOMNLG)

  • Samenvatting • 5 pagina's • 2024
  • This cheat sheet contains the most important information from the course and refers to pages in the full summary for extra details. Everything is clearly highlighted.
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  • €7,16
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Summary-  Natural Language Generation (INFOMNLG)
  • Summary- Natural Language Generation (INFOMNLG)

  • Samenvatting • 101 pagina's • 2024
  • Ook in voordeelbundel
  • This document includes a summary of all lectures, lecture notes, screenshots of important lecture slides and extra notes to help understand the contents and concepts better.
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Natural Language Generation Course Notes
  • Natural Language Generation Course Notes

  • Samenvatting • 22 pagina's • 2022
  • This document contains notes and summaries covering the content of the course Natural Language Generation within the Artificial Intelligence Master at Utrecht University.
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  • €8,49
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Natural Language Generation Exam Notes
  • Natural Language Generation Exam Notes

  • Samenvatting • 7 pagina's • 2022
  • This document contains notes and summaries covering the content of the course Natural Language Generation within the Artificial Intelligence Master at Utrecht University.
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  • €8,49
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Natural Language Generation Summary & Course Notes
  • Natural Language Generation Summary & Course Notes

  • Samenvatting • 15 pagina's • 2022
  • This document contains notes and summaries covering the content of the course Natural Language Generation within the Artificial Intelligence Master at Utrecht University. It is divided into two parts: Explainability and Fairness. It covers the following topics: - intro to nlg - nlg metrics and evaluation - commercial nlg - linguistics, pragmatics and the grecian maxims - REG algorithms
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