troy

# usage: redfin-images "http://www.redfin.com/WA/Seattle/123-Home-Row-12345/home/1234567"
function redfin-images() {
 wget -O - $1 | grep "full:" | awk -F \" '{print $4}' | xargs wget -
}

ttezel

#A Collection of NLP notes

##N-grams

###Calculating unigram probabilities:

P( w_i ) = count ( w_i ) ) / count ( total number of words )

In english..

phette23

#!/usr/bin/env fish
# similar script in Fish
# still under construction, need to quiet `git status` more effectively

function update -d 'Update git repo'
  git stash --quiet
  git pull
  git stash apply --quiet
end

acdha

#!/usr/bin/env PYTHONIOENCODING=utf-8 python
# encoding: utf-8
"""Git pre-commit hook which lints Python, JavaScript, SASS and CSS"""

from __future__ import absolute_import, print_function, unicode_literals

import os
import subprocess
import sys

softwaredoug

What I did to get Python 3.4.2 on Ubuntu 14.04. The stock version of Python 3 on Ubuntu is 3.4.0. Which is missing some of the best parts! (asyncio, etc). Luckily I discovered pyenv which solved my problem.

Install pyenv

Pyenv (not to be confused with pyvenv) is the Python equivelant of rbenv. It lets you configure which Python environment/version is available per directory, user, or other session variables.

I followed the instructions here to install pyenv in my home directory. Verbatem, those instructions are:

sudo apt-get install git python-pip make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev

Newmu

"""
The MIT License (MIT)

Copyright (c) 2015 Alec Radford

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is

Antrikshy

import random
import math

# Configure paths to your dataset files here
DATASET_FILE = 'data.csv'
FILE_TRAIN = 'train.csv'
FILE_VALID = 'validation.csv'
FILE_TESTS = 'test.csv'

# Set to true if you want to copy first line from main

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

mick001

library(MASS)       # Boston dataset
library(neuralnet)  # Neuralnet
library(plyr)       # Progress bar

#-------------------------------------------------------------------------------
# Cross validating function

crossvalidate <- function(data,hidden_l=c(5))
{
    # @params

calstad

Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning

This is just a quick list of resourses on TDA that I put together for @rickasaurus after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.

Survey Papers

Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

• Topology and Data by Gunnar Carlsson
• Barcodes: The Persistent Topology of Data by Robert Ghrist

Other Papers and Web Resources

• Extracting insights from the shape of complex data using topology A good introductory paper in Nature on the Mapper algorithm.