Text Analysis for Statistics & Data Science
Lectures
28
Keyness
Overview
Labs
1
Mosteller & Wallace
2
NLP Basics
3
Processing pipelines
4
Distributions
5
Collocations & Association Measures
6
Keyness
7
Part-of-Speech Tagging and Dependency Parsing
8
Logistic Regression
9
Multi-Dimensional Analysis
10
Cluster Analysis
11
Time Series
12
Texts, Algorithms, and Black-Boxes
13
Introduction to Vector Models and Word Embeddings
14
Geospacial Mapping: POP? SODA? or COKE?
15
Random Forest
Labs Sets
16
Lab Set 1
17
Lab Set 2
18
Lab Set 3
19
Lab Set 4
Report Templates
20
CBE 1
21
CBE 2
22
Final Project
23
Final Project Rubric
Lectures
24
Linguistic Facts of Life
25
LLMs History
26
Word Frequencies & Dispersions
27
Collocations
28
Keyness
29
Factor analysis and MDA
30
Cluster Analysis
31
Time Series
32
Sentiment Analysis
33
Embeddings
Lectures
28
Keyness
28
Keyness
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28.0.0.1
This lecture accompanies Lab 06.
27
Collocations
29
Factor analysis and MDA