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Machine Learning in Natural Language Processing, 7.5 ects

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.gitignore
.gitignore
 
 
Assignment 01 - Sentiment Polarity on Film Reviews.ipynb
Assignment 01 - Sentiment Polarity on Film Reviews.ipynb
 
 
Assignment 02 - Evaluating and Extending an RNN based Part-of-Speech Tagger.ipynb
Assignment 02 - Evaluating and Extending an RNN based Part-of-Speech Tagger.ipynb
 
 
Assignment 04 - Gendered Directions in Embeddings.ipynb
Assignment 04 - Gendered Directions in Embeddings.ipynb
 
 
Course logo (multiprocessing animation).ipynb
Course logo (multiprocessing animation).ipynb
 
 
Exercise 00 - Clever decision tree template.py
Exercise 00 - Clever decision tree template.py
 
 
Exercise 00 - Clever decision tree unittests.py
Exercise 00 - Clever decision tree unittests.py
 
 
Exercise 01 - Linear regression unittests.py
Exercise 01 - Linear regression unittests.py
 
 
Exercise 02 - Simplified logistic regression.py
Exercise 02 - Simplified logistic regression.py
 
 
Exercise 03 - Neural Network from Scratch.py
Exercise 03 - Neural Network from Scratch.py
 
 
Exercise 06 - K-means unittests.py
Exercise 06 - K-means unittests.py
 
 
LICENSE
LICENSE
 
 
Lecture 01 - Decision Trees.ipynb
Lecture 01 - Decision Trees.ipynb
 
 
Lecture 01 - Encoding example.ipynb
Lecture 01 - Encoding example.ipynb
 
 
Lecture 02 - Basis Functions.ipynb
Lecture 02 - Basis Functions.ipynb
 
 
Lecture 03 - k-Nearest Neighbours.ipynb
Lecture 03 - k-Nearest Neighbours.ipynb
 
 
Lecture 04 - Bayesian linear regression.ipynb
Lecture 04 - Bayesian linear regression.ipynb
 
 
Lecture 04 - Feedforward network training.ipynb
Lecture 04 - Feedforward network training.ipynb
 
 
Lecture 07 - CNN for text classification.ipynb
Lecture 07 - CNN for text classification.ipynb
 
 
Lecture 07 - Loading and Visualizing GloVe.ipynb
Lecture 07 - Loading and Visualizing GloVe.ipynb
 
 
Lecture 08 - Clustering methods.ipynb
Lecture 08 - Clustering methods.ipynb
 
 
Lecture 08 - Gaussian Mixture Model.ipynb
Lecture 08 - Gaussian Mixture Model.ipynb
 
 
Lecture 09 - Bayesian logistic regression.ipynb
Lecture 09 - Bayesian logistic regression.ipynb
 
 
Lecture 09 - Naive Bayes.ipynb
Lecture 09 - Naive Bayes.ipynb
 
 
Lecture 11 - Thug life.ipynb
Lecture 11 - Thug life.ipynb
 
 
README.md
README.md
 
 
Studium logo (multiprocessing animation).ipynb
Studium logo (multiprocessing animation).ipynb
 
 
Thug_life_glasses.png
Thug_life_glasses.png
 
 

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Code for 'Machine Learning in Natural Language Processing' (5LN708)

This repo contains material I've written for the course 'Machine Learning in Natural Language Processing' (7.5 ects, 5LN708) at Uppsala University. The code here is not intended to be a full course on its own, but a place where I publish code shown in the lectures, some exercises, and notebooks for the assignments.

Enrolled students can find slides etc at https://uppsala.instructure.com/courses/74791 .

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Machine Learning in Natural Language Processing, 7.5 ects

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