Spencer justmytwospence

## TextMining.ipynb

      
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                justmytwospence
                / TextMining.ipynb
            
            
              Created
              March 13, 2014 05:16
            
              
                Various applications of text mining. Includes multinomial naive Bayes, TFIDF vectorizer, cross-validation over pipelines, confusion matrix of classifications, cosine distances between documents, collocation matrices, graph visualization with NetworkX and Gephi, various uses of textutils.py, and connecting to the Twitter API.
              
          
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## Vectorization.ipynb

      
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                justmytwospence
                / Vectorization.ipynb
            
            
              Created
              February 26, 2014 05:23
            
              
                Vectorization for text mining. Includes the Porter Stemmer, a custom regular expression tokenizer, and the sklearn term frequency - inverse document frequency vectorizer.
              
          
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## bootstrap-template.html
<!DOCTYPE html>
<html>
  <head>
    <title>#!title#</title>
    <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
    <meta charset="utf-8">
    <meta http-equiv="X-UA-Compatible" content="IE=edge">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <!-- Latest compiled and minified CSS -->
    <link rel="stylesheet" href="http://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css">

## Logit.ipynb

      
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                justmytwospence
                / Logit.ipynb
            
            
              Created
              February 17, 2014 06:47
            
              
                Logistic regression with sci-kit learn. Second homework for MSAN 630. Learning curves, shuffle splits, L1 regularization, and more.
              
          
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## Rmagic.ipynb

      
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                justmytwospence
                / Rmagic.ipynb
            
            
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              August 29, 2015 13:55
            
              
                IPython is not just for Python! Master your interdisciplinary data-science-fu with IPython magic! View here: http://nbviewer.ipython.org/gist/justmytwospence/8750427
              
          
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## SVM.ipynb

      
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                justmytwospence
                / SVM.ipynb
            
            
              Created
              February 1, 2014 03:55
            
              
                First homework assignment for MSAN 630. All about training SVMs, including parameter grid search, leave one out cross validation, k-fold cross validation, 2 dimensional decision boundary plotting, RBF kernels, and more. View it here: http://nbviewer.ipython.org/gist/justmytwospence/8747722.
              
          
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## fontawesome.sty
% FontAwesome (http://fortawesome.github.com/Font-Awesome/) bindings for (Xe)LaTeX
% Author: Honza Ustohal <honza@egoistic.biz>
% A few icons added by: Spencer Boucher <spencer.g.boucher@gmail.com>
%
% Translation of FontAwesome's private range characters into XeTeX symbols. All icons are camel-cased and prefixed with 'fa', i.e. what was .icon-align-center the CSS version of FontAwesome becomes \faAlignCenter
% This might be reworked into a full blown package in the near future
%
% Prerequisite:
% XeLaTeX, FontAwesome installed as a system font accessible by XeLaTeX
%

## direct-download.php
<?php
    $actual_file_name = "path/to/foo.pdf";
    $saved_file_name = "foo-bar.pdf"

    header("Content-Type: application/pdf");
    header("Content-Disposition: attachment; filename=$saved_file_name");
    header("Content-Length: " . filesize($actual_file_name));

    readfile($actual_file_name);
    exit;

## stratified-sample.R
stratified_sample <- function(df, size = .5, .by, seed = 37L) {
  require(plyr)
  set.seed(seed)
  df.sample <- ddply(df, .by,
                     function(x) {
                       if (size < 1) { size <- size * nrow(x) }
                       return(x[sample(nrow(x), size = size),])
                     },
                     .progress = 'text')
  return(df.sample)

## ignore-big
find . -size +1G | cat >> .gitignore
	<!DOCTYPE html>
	<html>
	<head>
	<title>#!title#</title>
	<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
	<meta charset="utf-8">
	<meta http-equiv="X-UA-Compatible" content="IE=edge">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<!-- Latest compiled and minified CSS -->
	<link rel="stylesheet" href="http://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css">
	% FontAwesome (http://fortawesome.github.com/Font-Awesome/) bindings for (Xe)LaTeX
	% Author: Honza Ustohal <honza@egoistic.biz>
	% A few icons added by: Spencer Boucher <spencer.g.boucher@gmail.com>
	%
	% Translation of FontAwesome's private range characters into XeTeX symbols. All icons are camel-cased and prefixed with 'fa', i.e. what was .icon-align-center the CSS version of FontAwesome becomes \faAlignCenter
	% This might be reworked into a full blown package in the near future
	%
	% Prerequisite:
	% XeLaTeX, FontAwesome installed as a system font accessible by XeLaTeX
	%
	<?php
	$actual_file_name = "path/to/foo.pdf";
	$saved_file_name = "foo-bar.pdf"

	header("Content-Type: application/pdf");
	header("Content-Disposition: attachment; filename=$saved_file_name");
	header("Content-Length: " . filesize($actual_file_name));

	readfile($actual_file_name);
	exit;
	stratified_sample <- function(df, size = .5, .by, seed = 37L) {
	require(plyr)
	set.seed(seed)
	df.sample <- ddply(df, .by,
	function(x) {
	if (size < 1) { size <- size * nrow(x) }
	return(x[sample(nrow(x), size = size),])
	},
	.progress = 'text')
	return(df.sample)