Chris Strelioff cstrelioff

counter exampe with external js files

This is an example of using external javascript files and using the jquery ready() method to execute code when the DOM is loaded (ie, ready). To get this to work:

Download index.html, mycode.js, and jquery-1.11.3.min.js to your computer.
- Note that I have not include the jquery file here, you'll have to grab this from other examples at the course website.
Put all of the files in the same directory or folder.
Open index.html in your browser and things should work as before, except for the fact that we are using external javascript files

write LDA topic probabilities to csv

This gist shows one way to write the topic distribution for each document to a csv file-- this can be loaded into Excel, or similar program, for viewing. The topic distribution considered here is created by the Python package lda. See my blog post on lda for more information.

decision trees: cross-validation

This script provides an example of using cross-validation to fine-tune parameters for learning a decision tree with scikit-learn.

A blog post about this code is available here, check it out!

Requirements

decision trees: scikit-learn + pandas

This script provides an example of learning a decision tree with scikit-learn. Pandas is used to read data and custom functions are employed to investigate the decision tree after it is learned. Grab the code and try it out.

A blog post about this code is available here, check it out!

A script that replicates all examples in my blog post on revisiting the Bayesian medical tests example-- using Python and Lea to do some probabilistic programming: Medical test/Lea post

Run all the examples

    $ python lea_ex02.py

A script that replicates all examples in my blog post using Python and Lea to do some probabilistic programming: Lea post

Run all the examples

    $ python lea_ex01.py

process corpus for lda

In a blog post I wrote about the python package lda, see here, I used the pre-processed data (included with the lda package) for the example. I have since received many questions regarding the document-term matrix, the titles, and the vocabulary-- where do they come from? This gist will use the textmining package to (hopefully) help answer these types of questions.

overview

A basic responsive web page, following the ideas presented in Learning Responsive Web Design by Clarissa Peterson.

	<!DOCTYPE html>
	<html>
	<head>
	<title>responsive svg bar chart</title>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">

	<!-- styles: should have reset.css first -->
	<link rel="stylesheet" href= "reset.css">
	<link rel="stylesheet" href= "main.css">