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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) |
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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 = [], [] |
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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 = '' |
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''' | |
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 |
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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 |
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// 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 | |
}; |
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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) |
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//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 |