Skip to content
Jason Stephens edited this page Sep 21, 2016 · 11 revisions

My notes wiki for shiffman's a2z-f16

javascript for text-based data


my notes wiki pages

my a2z gong-fu via gh-pages

course overview

This course focuses on programming strategies and techniques behind procedural analysis and generation of text-based data. We'll explore topics ranging from evaluating text according to its statistical properties to the automated production of text with probabilistic methods to text visualization. Students will learn server-side and client-side JavaScript programming and develop projects that can be shared and interacted with online. There will be weekly homework assignments as well as a final project.

Info

  • Daniel Shiffman, Tuesdays, 9:00am-11:30am
  • All class dates
  • Office Hours
  • In addition to the ITP physical class, I am running an online version of the class for Patreon subscribers. ITP students will receive a slack invite should they want to participate. YouTube live stream sessions TBA.

Mailing List

Week 1 - Intro

Week 2 -- Regular Expressions

  • Also
    • multiple DOMs + multiple event
    • rita.js -- similar and rhyming, etc.
  • Regular Expressions
    • meta-characters
      • position
      • single character
      • quantifiers
      • character classes
      • alternation
      • capturing groups and back reference
    • Regex in atom editor
    • Regex in JS:
      • Regex: test(), exec()
      • String: match()
    • Splitting with regex: split()
    • Replace with regex: replace()
    • randexp.js
  • Homework Assignment -- TBA

Week 3 -- Data/API Workshop

  • APIs
  • Working with google sheets
  • Parse (doesn't exist anymore, something else?)

Week 4 -- Intro to Node and Twitter Bots

  • Server side programming with Node
  • Node data persistence
  • html scraping
  • How to make a Twitter bot
  • Start working on Twitter Bot project

Week 5 - Text Analysis Workshop

  • In class, we'll build a simple concordance together as well as demonstrate and discuss TF/IDF and Bayesian analysis.
  • Simple Concordance
  • TF/IDF
  • Bayesian Analysis
  • Node text analysis packages

Week 6 - Show Twitter Bots

Week 7 - Text Generation: Markov chains

  • Using google sheets for text input
  • ngrams and markov chains

Week 8 - Text Generation: Grammars

  • Tracery by Kate Compton
  • Context free grammars

Week 9 - Chrome Extensions

Week 10 - Building your own API in Node

Week 11 - Final Project Proposals part 1

Week 12 - Final Project Proposals part 2

Week 13 - User Testing

Week 14 - Final Presentations

References and Inspiration

Tools

JS reference books

Learning / Intro

Tools

Requirements

  • You are required to attend all class meetings and submit all weekly assignments and a final project.
  • Grading (pass/fail) will be based on a combination of factors:
    • Attendance, participation in class discussion, and engagement in other students' projects (25%)
    • Quality of assignments (50%)
    • Final Project (25%)