Skip to content

Interactive demos to learn concepts in ML, NLP, and AI

Notifications You must be signed in to change notification settings

dlab-berkeley/demos

Repository files navigation

D-Lab Interactive Demos

License: CC BY 4.0

Overview

This repository contains interactive browser-based demonstrations for teaching computational concepts. These standalone HTML tutorials require no installation and can be viewed directly in any modern web browser.

Demos

  • Git & GitHub - Version control, branching, and collaboration workflows
  • Web APIs - REST principles, authentication, and rate limiting
  • Web Scraping - Extracting data from websites with Python and BeautifulSoup
  • TF-IDF - Term frequency-inverse document frequency explained
  • TF-IDF Game - Interactive word detective mystery game
  • Word Embeddings - How computers learn word meanings through context
  • Transformer Attention - Understanding attention mechanisms in AI models
  • ML Classification - How algorithms learn decision boundaries to categorize data
  • Causal Inference - Why correlation doesn't imply causation
  • Regular Expressions - Interactive pattern matching for text

Usage

Open index.html in a browser or visit the hosted version at dlab-berkeley.github.io/demos.

About D-Lab

D-Lab works with Berkeley faculty, research staff, and students to advance data-intensive social science and humanities research. Visit dlab.berkeley.edu to learn more.

Contributors

  • Tom van Nuenen

About

Interactive demos to learn concepts in ML, NLP, and AI

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 2

  •  
  •