Lecture: Natural Language Processing

Lecture: Natural Language Processing

Administrative information

Title Natural Language Processing
Duration 60 - 70 minutes
Module A
Lesson Type Lecture
Focus Lecture - AI Modelling
Topic Statistical methods for NLP and text classification

 

Keywords

NLP,Natual Language Processing,Computational Linguistics,

 

Learning Goals

  • Students understand the basic concepts of Natural Language Processing
  • Students learn NLP use cases
  • Students get familiar with various NLP tools and concepts

 

Expected Preparation

Learning Events to be Completed Before

None.

Obligatory for Students

  • A review of basic statistics

Optional for Students

  • Review of Python Programming Language

References and background for students:

Lesson Materials

 

The materials of this learning event are available under CC BY-NC-SA 4.0.

 

Instructions for Teachers

You can base this class around the slides. The material is suggested but can be adapted.

Outline

Time schedule
Duration (Min) Description Concepts Activity Material
5 Introduction to Natural Language Processing, goals, methods and challenges computer linguistics, natural language processing    
5 Processing Natural Language Text: Use cases corpus, segmentation, tokenization, concordance    
10 Regular Expressions, Text Normalisation language modeling, edit distance    
15 N-gram Models Sequences of words as a Markov process    
5 Chain Rule of Probality General product rule    
10 Markov and Maximum Likelihood Estimation Markov chain - stochastic model    
5 Evaluation Language Models Perplexity    
5 Naive Bayes Classifier Probabilistic classifiers Preparing the lab excercise  

 

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.

The materials of this learning event are available under CC BY-NC-SA 4.0

 

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities

HCAIM Consortium

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Auteur
HCAIM Consortium
Laatst gewijzigd
2024-05-15 11:03:20
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Gebruikte Wikiwijs Arrangementen

HCAIM Consortium. (z.d.).

Acknowledgement

https://maken.wikiwijs.nl/198386/Acknowledgement

HCAIM Consortium. (z.d.).

Lecture: Duty Ethics

https://maken.wikiwijs.nl/198966/Lecture__Duty_Ethics

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