https://github.com/jnxf/nlp-dl

:abcd: Natural Language Processing and Deep Learning
https://github.com/jnxf/nlp-dl

deep-learning false-friends natural-language-processing notes phonetics

Last synced: 11 months ago
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:abcd: Natural Language Processing and Deep Learning

• Host: GitHub
• URL: https://github.com/jnxf/nlp-dl
• Owner: JnxF
• License: mit
• Created: 2020-07-13T12:04:45.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-08-19T19:13:10.000Z (almost 6 years ago)
• Last Synced: 2025-03-27T05:14:15.997Z (about 1 year ago)
• Topics: deep-learning, false-friends, natural-language-processing, notes, phonetics
• Language: Python
• Homepage: https://learnit.itu.dk/course/view.php?id=3019331
• Size: 21.5 MB
• Stars: 3
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# Natural Language Processing and Deep Learning

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This repository compiles the different activities that have been carried out during course at the IT University of Copenhagen in summer 2020: class notes, assignments and a final project.

## Final project

I have written a paper regarding false friends as my final project:

[_Dangerous Liaisons: the Impact of Phonetics in False Friends Detection Among Romance Languages_](project/)

## Assignments

1. [HMM Part-of-speech tagger](assignments/01-hmm-part-of-speech-tagger)

2. [LSTM Part-of-speech tagger](assignments/02-lstm-part-of-speech-tagger)

## Notes

### A. Languages

0. [Introduction](notes/A-Language/00-Introduction.md)

1. [Languages](notes/A-Language/01-Levels_of_linguistics.md)

2. [Tokens](notes/A-Language/02-Tokens.md)

3. [Word representations](notes/A-Language/03-Word_representations.md)

4. [Formal definitions](notes/A-Language/04-Formal_definitions.md)

5. [WordNet](notes/A-Language/05-WordNet.md)

6. [Parts of Speech](notes/A-Language/06-Parts_of_Speech.md)

7. [Language models](notes/A-Language/07-Language_models.md)

8. [Markov models](notes/A-Language/08-Markov_models.md)

9. [Sequence modeling](notes/A-Language/09-Sequence_modeling.md)

### B. Machine learning and deep learning

0. [Introduction](notes/B-Machine_learning_and_deep_learning/00-Introduction.md)

1. [Perceptrons](notes/B-Machine_learning_and_deep_learning/01-Perceptrons.md)

2. [Multilayer neural networks](notes/B-Machine_learning_and_deep_learning/02-Multilayer_neural_networks.md)

3. [Gradient descent](notes/B-Machine_learning_and_deep_learning/03-Gradient_descent.md)

4. [LSTM](notes/B-Machine_learning_and_deep_learning/04-Long_short_term_memory.md)

5. [Word representations](notes/B-Machine_learning_and_deep_learning/05-Word_representations.md)

6. [Clustering](notes/B-Machine_learning_and_deep_learning/06-Clustering.md)

### C. Advanced topics in NLP

1. [Transformers](notes/C-Advanced_topics_in_NLP/01-Transformers.md)

2. [Social media](notes/C-Advanced_topics_in_NLP/02-Social_media.md)

3. [Entity recognition](notes/C-Advanced_topics_in_NLP/03-Entity_recognition.md)

4. [Statistical Machine Learning](notes/C-Advanced_topics_in_NLP/04-Statistical_machine_translation.md)

5. [Conversational agents](notes/C-Advanced_topics_in_NLP/05-Conversational_agents.md)

6. [Transfer learning](notes/C-Advanced_topics_in_NLP/06-Transfer_learning.md)

## Exercises

1. [Segmenting chinese text](exercises/01-chinese_segmentation)

2. [POS tagger](exercises/02-pos-tagger)

3. [Perceptron exercises](exercises/03-perceptrons)

4. [Naive Bayes](exercises/04-naive-bayes)