From 0456c5fe7299d01b6cb7e5d6b3a89aa046a1093b Mon Sep 17 00:00:00 2001 From: Tom van Nuenen Date: Thu, 8 May 2025 15:20:02 -0700 Subject: [PATCH 1/2] Update README.md --- README.md | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index c458986..94ac868 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,10 @@ -# D-Lab Python Text Analysis Workshop +# D-Lab Python NLP Fundamentals Workshop [![Datahub](https://img.shields.io/badge/launch-datahub-blue)](https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Text-Analysis&urlpath=lab%2Ftree%2FPython-Text-Analysis%2F&branch=main) [![Binder](https://img.shields.io/badge/launch-binder-579aca.svg?logo=data:image/png;base64,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)](https://mybinder.org/v2/gh/dlab-berkeley/Python-Text-Analysis/HEAD) [![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/) -This repository contains the materials for the D-Lab Python Text Analysis +This repository contains the materials for the D-Lab Python NLP Fundamentals workshop. We recommend attending Python Fundamentals, Python Data Wrangling, and Python Machine Learning Fundamentals prior to this workshop. @@ -12,18 +12,14 @@ Check D-Lab's [Learning Pathways](https://dlab-berkeley.github.io/dlab-workshops ## Workshop Goals -This 3-part workshop will prepare participants to move forward with research that uses text -analysis, with a special focus on social science applications. We explore -fundamental approaches to applying computational methods to text in Python. We -cover some of the major packages used in natural language processing, including -scikit-learn, NLTK, spaCy, and Gensim. +This 3-part workshop will prepare participants to move forward with research using Natural Language Processing (NL), with a special focus on social science applications. We explore fundamental approaches to applying computational methods to text in Python. We cover some of the major packages used in NLP, including scikit-learn, NLTK, spaCy, and Gensim. 1. **Part 1: Preprocessing.** How do we standardize and clean text documents? Text data is noisy, and we often need to develop a pipeline in order to standardize the data to better facilitate computational modeling. You will learn common and task-specific operations of preprocessing, becoming familiar with commonly used NLP packages and what they are capable of. You will also learn about tokenizers, and how they have changed since the advent of Large Language Models. -2. **Part 2: Bag-of-words.** In order to do any computational analysis on the text data, we need to devise approaches to convert text into a +2. **Part 2: Bag-of-words.** In order to do any computational analysis on text data, we need to devise approaches to convert text into a numeric representation. You will learn how to convert text data to a frequency matrix, and how TF-IDF complements the Bag-of-Words representation. You will also learn about parameter settings of a vectorizer and apply sentiment classification to vectorized text data. 3. **Part 3: Word Embeddings.** Word Embeddings underpin nearly all modern language models. In this workshop, you will learn the differences From c311c146bdf453a7794bded989f67fb177d06580 Mon Sep 17 00:00:00 2001 From: Tom van Nuenen Date: Tue, 17 Jun 2025 12:12:06 -0700 Subject: [PATCH 2/2] Update README.md --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 94ac868..5db11ba 100644 --- a/README.md +++ b/README.md @@ -157,6 +157,7 @@ expertise. - [Mingyu Yuan](https://github.com/mingyu-yuan) - [Pratik Sachdeva](https://github.com/pssachdeva) +- [Tom van Nuenen](https://github.com/tomvannuenen) - [Ben Gebre-Medhin](http://gebre-medhin.com) - [Laura Nelson](http://www.lauraknelson.com) - [Teddy Roland](https://teddyroland.com/about/)