lobstrio

#!/usr/bin/python3
# coding: utf-8

import requests
from bs4 import BeautifulSoup
from scrapy import Selector
import csv
import datetime

pandafulmanda

Python3 Virtualenv Setup

Requirements

• Python 3
• Pip 3

$ brew install python3

alejandrofloresm

# Code example for:
# Hello World - Machine Learning Recipes #1 - Google Developers
# https://www.youtube.com/watch?v=cKxRvEZd3Mw

from sklearn import tree

# Bumpy = 0, Smooth = 1
features = [[140, 1], [130, 1], [150, 0], [170, 0]]
# Apple = 0, Orange = 1
labels = [0, 0, 1, 1]

karpathy

"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code

class LSTM:
  
  @staticmethod
  def init(input_size, hidden_size, fancy_forget_bias_init = 3):

s0enke

<?php
$values = array(
    'true' => true,
    'false' => false,
    '1' => 1,
    '0' => 0,
    '-1' => -1,
    '"true"' => "true",
    '"false"' => "false",
    '"1"' => "1",

ungoldman

How do you POST a JSON file with curl??

You can post a json file with curl like so:

curl -X POST -H "Content-Type: application/json" -d @FILENAME DESTINATION

so for example:

ccorcos

from pylab import *
from pprint import pprint


def arrayToList(arr):
    if type(arr) == type(array([])):
        return arrayToList(arr.tolist())
    elif type(arr) == type([]):
        return [arrayToList(a) for a in arr]
    else:

Jim-Holmstroem

from hashlib import sha1
import numpy
arr=numpy.zeros((256,256,4))
sha1(arr)

dokipen

import requests
import sys

for i in range(1,10000):
    response = requests.post('http://apply.embed.ly/1', data={'answer': str(i)})
    if response.status_code == 302:
        print i
        sys.exit(0)

reyjrar

(* 
 * New-iTerm-Window.scpt
 * 
 * Intended for use with QuickSilver
 *  I mapped option-y to running this script to create
 *  a new iTerm window on the current workspace
 *
 * Based on much Googling - very little "original" code here
 *   Comments/Suggestions to brad.lhotsky@gmail.com
 *)