joskid

import json, requests, simplegeo
from simplegeo.models import Record

client = simplegeo.Client('your-key', 'your-secret')

firehose = 'http://api.plancast.com/02/plans/firehose.json?extensions=place'
resp = requests.get(url=firehose)
data = json.load(resp)

plans = data['plans']

joskid

### Install some packages. Ignore the errors.

aptitude install binutils libgdal1-1.5.0 postgresql-8.3-postgis postgresql-server-dev-8.3 python-psycopg2 python-setuptools

### Make connecting to postgres easier

echo "local all all trust" > /etc/postgresql/8.3/main/pg_hba.conf 
invoke-rc.d postgresql-8.3 reload

### Become the Postgres user to create a spatial template database:

joskid

"""ajaxgoogle.py - Simple bindings to the AJAX Google Search API
(Just the JSON-over-HTTP bit of it, nothing to do with AJAX per se)
http://code.google.com/apis/ajaxsearch/documentation/reference.html#_intro_fonje
brendan o'connor - gist.github.com/28405 - anyall.org"""
try:
  import json
except ImportError:
  import simplejson as json

import urllib, urllib2

joskid

4 # number of states
START
COLD
HOT
END

3 # size of vocab
1
2
3

joskid

"""
A really stupid python template language inspired by coffeekup, markaby.
Do not use this code, it will ruin your day.  A byproduct of insomnia.

TL;DR
-----

This module defines a template language that allows us to do:

    d = Doc()

joskid

General

Tutorials on topics in machine learning

Hashing Searching Sketching.

Parallel Machine Learning

http://graphlab.org/

AdaBoost

joskid

# Mathieu Blondel, October 2010

import numpy as np
from numpy import linalg

def linear_kernel(x1, x2):
    return np.dot(x1, x2)

def polynomial_kernel(x, y, p=3):
    return (1 + np.dot(x, y)) ** p

joskid

// define inside file timetest.m
function blank = timetest(x, y, MAX_ITR)
    m = length(y);
    x = [ones(m, 1) x];
    theta = zeros(size(x(1,:)))'; % initialize fitting parameters
    alpha = 0.07;
    
    for num_iterations = 1:MAX_ITR
        grad = (1/m).* x' * ((x * theta) - y);
        theta = theta - alpha .* grad;

joskid

/* jQuery Tiny Pub/Sub - v0.7 - 10/27/2011
 * http://benalman.com/
 * Copyright (c) 2011 "Cowboy" Ben Alman; Licensed MIT, GPL */

(function($) {

  var o = $({});

  $.subscribe = function() {
    o.on.apply(o, arguments);

joskid

"""
(C) Mathieu Blondel - 2010

Implementation of the collapsed Gibbs sampler for
Latent Dirichlet Allocation, as described in

Finding scientifc topics (Griffiths and Steyvers)
"""

import numpy as np