🚀 Costin Chitic

Search

SearchSearch

Recent Notes

  • BoQ: A Place is Worth a Bag of Learnable Queries

    Oct 09, 2026

  • Co-Me: Confidence Guided Token Merging for Visual Geometric Transformers

    Oct 09, 2026

  • Sinkhorn Algorithm for Locally Aggregated Descriptors (SALAD)

    Oct 09, 2026

  • Bootstrap Aggregation (Bagging)

    Oct 08, 2026

  • Random Forest

    Oct 08, 2026

Home

❯

notes

❯

Natural Language Processing

Natural Language Processing

Oct 09, 20261 min read

I’m taking this course as part of my Q1 curriculum at Twente.

Subjects covered so far

  • Words and Tokens
  • N-grams Language Model and Text Classification
  • Sentiment Analysis and Naive Bayes
  • Hidden Markov Models for PoS tagging and NER
  • Vector Semantics and Embeddings
  • Transformers
  • Contextual Word Embeddings and Transformers
  • Constituency Grammars
  • Constituency Parsing

Reference material:

  • 3rd edition of the book Speech and Language Processing by Dan Jurafsky and James H. Martin.

Graph View

Backlinks

  • Vector Semantics and Embeddings
  • Contextual Word Embeddings and Transformers
  • Constituency Grammars
  • Introduction to Transformers in Deep Learning
  • University of Twente

Created with Quartz v4.2.3 © 2026

  • GitHub
  • Discord Community