HarshTrivedi

import torch
from torch import LongTensor
from torch.nn import Embedding, LSTM
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence

## We want to run LSTM on a batch of 3 character sequences ['long_str', 'tiny', 'medium']
#
#     Step 1: Construct Vocabulary
#     Step 2: Load indexed data (list of instances, where each instance is list of character indices)

bowbowbow

import json
import random
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.linear_model import LogisticRegression
from sklearn import preprocessing

json_data = open('./dataset.json').read()
tweets = json.loads(json_data)

tweets_train, tweets_test = [], []

ihsgnef

import numpy as np
import matplotlib
import matplotlib.pyplot as plt

def colorize(words, color_array):
    # words is a list of words
    # color_array is an array of numbers between 0 and 1 of length equal to words
    cmap = matplotlib.cm.get_cmap('RdBu')
    template = '<span class="barcode"; style="color: black; background-color: {}">{}</span>'
    colored_string = ''

seanbehan

'''
Run the following commands (bc. gists don't allow directories)

pip install flask django dj-database-url psycopg2

mkdir -p app/migrations
touch app/__init__.py app/migrations/__init__.py
mv models.py app/
python manage.py makemigrations
python manage.py migrate

telbiyski

sudo apt-get update
sudo apt-get install build-essential chrpath libssl-dev libxft-dev -y
sudo apt-get install libfreetype6 libfreetype6-dev -y
sudo apt-get install libfontconfig1 libfontconfig1-dev -y
cd ~
export PHANTOM_JS="phantomjs-2.1.1-linux-x86_64"
wget https://github.com/Medium/phantomjs/releases/download/v2.1.1/$PHANTOM_JS.tar.bz2
sudo tar xvjf $PHANTOM_JS.tar.bz2
sudo mv $PHANTOM_JS /usr/local/share
sudo ln -sf /usr/local/share/$PHANTOM_JS/bin/phantomjs /usr/local/bin

developer-sdk

// iconv-lite 를 이용하여 한글이 깨져서 출력될때 수정하는 방법
var request = require("request");
var cheerio = require('cheerio');
var iconv  = require('iconv-lite');
 
var requestOptions  = { method: "GET"
                ,uri: "http://news.naver.com/main/list.nhn?mode=LS2D&mid=shm&sid1=105&sid2=731"
                ,headers: { "User-Agent": "Mozilla/5.0" }
                ,encoding: null
            };

alexcasalboni

Google Vision API Examples and Python utilities

Label Detection Examples

Face Detection Examples

moeseth

from pydub import AudioSegment
from matplotlib import pyplot as plot
from PIL import Image, ImageDraw
import numpy as np
import os

src = "./test.mp3"

audio = AudioSegment.from_file(src)
data = np.fromstring(audio._data, np.int16)

pleaseshutup

//Thanks to:
//http://www.benjiegillam.com/2012/06/node-dot-js-ssl-certificate-chain/

//For the code to pass a CA bundle (multiple certs in one file) as an array 
//which fixes certificate errors on some browsers when doing https.createServer(options


//This is how you can fix that with nodejitsu's http-proxy when using SNI
// to have a server listening and returning multiple ssl certs