bluenote10

trait CrossProduct[A,B,C] {
  def cross( as: Traversable[A], bs: Traversable[B] ): Traversable[C]
}

trait LowPriorityCrossProductImplicits {
  private type TV[X] = Traversable[X]

  implicit def crosser2[A,B] = new CrossProduct[A,B,(A,B)] {
    def cross( as: TV[A], bs: TV[B] ): TV[(A,B)] = for { a <- as; b <- bs } yield (a, b)
  }

kljensen

# -*- coding: utf-8 -*-
""" Small script that shows hot to do one hot encoding
    of categorical columns in a pandas DataFrame.

    See:
    http://scikit-learn.org/dev/modules/generated/sklearn.preprocessing.OneHotEncoder.html#sklearn.preprocessing.OneHotEncoder
    http://scikit-learn.org/dev/modules/generated/sklearn.feature_extraction.DictVectorizer.html
"""
import pandas
import random

iambibhas

Here is a list of scopes to use in Sublime Text 2 snippets - 

ActionScript: source.actionscript.2
AppleScript: source.applescript
ASP: source.asp
Batch FIle: source.dosbatch
C#: source.cs
C++: source.c++
Clojure: source.clojure
CoffeeScript: source.coffee

gsomoza

#!bash.exe
export SSH_AUTH_SOCK=/tmp/.ssh-socket
echo ;
echo Starting connection with ssh-agent...
ssh-add -l 2>&1 >/dev/null
if [ $? = 2 ]; then
  rm -f /tmp/.ssh-script /tmp/.ssh-agent-pid /tmp/.ssh-socket
  # Exit status 2 means couldn't connect to ssh-agent; start one now
  echo Creating new ssh-agent...
  ssh-agent -a $SSH_AUTH_SOCK > /tmp/.ssh-script

japerk

Sentence Tokenization

>>> from nltk import tokenize
>>> para = "Hello. My name is Jacob. Today you'll be learning NLTK."
>>> sents = tokenize.sent_tokenize(para)
>>> sents
['Hello.', 'My name is Jacob.', "Today you'll be learning NLTK."]