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UT Computational Linguistics
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Contents
1
Python worksheets
1.1
General introduction to Python
1.2
Python and computational semantics
1.3
Other Python demos
2
R worksheets
3
Variational inference
Python worksheets
General introduction to Python
Worksheet: First steps in Python
Worksheet: Building your own Python functions
Worksheet: Python conditions, lists, and loops
Python list comprehensions
Python dictionaries
Worksheet: Reading and writing files in Python
Worksheet: Sorting in Python
Python worksheet: regular expressions
Python worksheet: accessing and processing text
Python and computational semantics
A very simple distributional model
Demo: The building blocks of a distributional model
Python demo: gensim
Python demo: predicting word similarity
Python demo: using a pre-trained space
Demo: computational semantics in NLTK
Other Python demos
Hidden Markov Models for POS-tagging in Python
Demo: the forward-backward algorithm
Language models in Python
R worksheets
Getting started with R
Data exploration
R worksheet: plotting
R worksheets: merge and aggregate
R worksheet: descriptive statistics
R worksheet: contingency tables
R code: reading, preprocessing and counting text.
R code: the t-test
R worksheet: influential datapoints
R code: nonparametric tests
R code: Correlation and linear regression
R code: linear regression
R code: more linear regression
R code: logistic regression
R code: model comparison
R code: ANOVA
R code: classification and cross-validation
R code: classification with Naive Bayes
R code: classification examples
R code: clustering
Topic modeling: a demo
Variational inference
Variational LDA tutorial
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