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John Berryman JnBrymn

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JnBrymn / SearchAsYouType.html
Created June 8, 2013 04:00
This is a demo search UI for demonstrating Search As You Type with Solr.
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>search as you type</title>
<link rel="stylesheet" href="http://code.jquery.com/ui/1.10.3/themes/smoothness/jquery-ui.css" />
<script src="http://code.jquery.com/jquery-1.9.1.js"></script>
<script src="http://code.jquery.com/ui/1.10.3/jquery-ui.js"></script>
<style>
@JnBrymn
JnBrymn / SemanticAnalyzer.py
Created July 29, 2013 03:53
Spin up a Solr, ingest some documents, and then run Latent Semantic Analysis and auto generate related words for each of your documents. For instance, a document with "darth vader" will have generated words such as "anakin", "yoda", and "jedi".
import requests
from collections import deque
class SolrTermVectorCollector(object):
def __pathToTvrh(self, solrUrl, collection):
import urlparse
userSpecifiedUrl = urlparse.urlsplit(solrUrl)
schemeAndNetloc = urlparse.SplitResult(scheme=userSpecifiedUrl.scheme,
netloc=userSpecifiedUrl.netloc,
path='',
query='',
@JnBrymn
JnBrymn / DocumentClassifier.ipynb
Last active December 24, 2015 01:29
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@JnBrymn
JnBrymn / index.html
Last active December 26, 2015 00:09
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>jQuery UI Slider - Default functionality</title>
<link rel="stylesheet" href="http://code.jquery.com/ui/1.10.3/themes/smoothness/jquery-ui.css" />
<script src="http://code.jquery.com/jquery-1.9.1.js"></script>
<script src="http://code.jquery.com/ui/1.10.3/jquery-ui.js"></script>
<link rel="stylesheet" href="/resources/demos/style.css" />
@JnBrymn
JnBrymn / fakeData.js
Last active August 29, 2015 13:56
var crypto = require('crypto');
//varies from -1 t0 1
var pow2_31 = Math.pow(2,31);
var randNum = function(t,seed) {
var shasum = crypto.createHash('sha1');
return shasum.update(""+seed+t).digest().readUInt32LE(0)/pow2_31-1;
}
var randNumGenMaker = function(seed) {
@JnBrymn
JnBrymn / neo performance test
Created March 21, 2014 12:56
This tests 3 different algorithms for insert a user with their friends.
{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
@JnBrymn
JnBrymn / MarkovModel.py
Last active August 29, 2015 13:57
Simple Markov Model
from collections import defaultdict
import random
class MarkovModel(object):
"""
Takes iterator of tokens and makes a markov model of the tokens. n is the "order" of the model
None is a special token that serves as a sort of delimiter of phrases.
"""
@classmethod
def _tokenizer(cls,text,token_delim):
@JnBrymn
JnBrymn / biz-intel.ipynb
Created April 29, 2014 20:37
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@JnBrymn
JnBrymn / sarama_example.go
Last active August 29, 2015 14:03
package main
import (
"fmt"
"github.com/Shopify/sarama" //GIT hash = b3d9702dd2d2cfe6b85b9d11d6f25689e6ef24b0
"time"
)
var groupName = "trash"
var topicName = "event"
@JnBrymn
JnBrymn / MarkovModel.js
Last active August 29, 2015 14:04
/* MarkovModel creates a Markov model of text (or tokens) and allow you to generate new
* text from the model. It takes two optional arguments:
*
* tokenizer - a function that takes a string and returns an array of tokens
* defaults to a tokenizer that breaks on whitespace and lowercases everything
* shingle_n - the number of tokens that make up a state in the markov model
* the higher the number the more realistic the generated data, but the more
* training data required
* defaults to 1
* join_str - string used to join text together