n3wtron

#!/usr/bin/python
'''
	Author: Igor Maculan - n3wtron@gmail.com
	A Simple mjpg stream http server
'''
import cv2
import Image
import threading
from BaseHTTPServer import BaseHTTPRequestHandler,HTTPServer
from SocketServer import ThreadingMixIn

addyosmani

Update May 2017

Eric Bidelman has documented some of the common workflows possible with headless Chrome over in https://developers.google.com/web/updates/2017/04/headless-chrome.

Update

If you're looking at this in 2016 and beyond, I strongly recommend investigating real headless Chrome: https://chromium.googlesource.com/chromium/src/+/lkgr/headless/README.md

Windows and Mac users might find using Justin Ribeiro's Docker setup useful here while full support for these platforms is being worked out.

kiyukuta

#coding: utf8
"""
1. Download this gist.
2. Get the MNIST data. 
    wget http://deeplearning.net/data/mnist/mnist.pkl.gz 
3. Run this code.
    python autoencoder.py 100 -e 1 -b 20 -v 
"""
import numpy
import argparse

parosky

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import csv
import codecs
import numpy as np
import MeCab

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.cluster import KMeans, MiniBatchKMeans

andreas-h

# -*- coding: utf-8 -*-

import datetime

from numpy import asarray, ceil
import pandas
import rpy2.robjects as robjects

def stl(data, ns, np=None, nt=None, nl=None, isdeg=0, itdeg=1, ildeg=1,
        nsjump=None, ntjump=None, nljump=None, ni=2, no=0, fulloutput=False):

gruber

The regex patterns in this gist are intended only to match web URLs -- http,
https, and naked domains like "example.com". For a pattern that attempts to
match all URLs, regardless of protocol, see: https://gist.github.com/gruber/249502


# Single-line version:

(?i)\b((?:https?:(?:/{1,3}|[a-z0-9%])|[a-z0-9.\-]+[.](?:com|net|org|edu|gov|mil|aero|asia|biz|cat|coop|info|int|jobs|mobi|museum|name|post|pro|tel|travel|xxx|ac|ad|ae|af|ag|ai|al|am|an|ao|aq|ar|as|at|au|aw|ax|az|ba|bb|bd|be|bf|bg|bh|bi|bj|bm|bn|bo|br|bs|bt|bv|bw|by|bz|ca|cc|cd|cf|cg|ch|ci|ck|cl|cm|cn|co|cr|cs|cu|cv|cx|cy|cz|dd|de|dj|dk|dm|do|dz|ec|ee|eg|eh|er|es|et|eu|fi|fj|fk|fm|fo|fr|ga|gb|gd|ge|gf|gg|gh|gi|gl|gm|gn|gp|gq|gr|gs|gt|gu|gw|gy|hk|hm|hn|hr|ht|hu|id|ie|il|im|in|io|iq|ir|is|it|je|jm|jo|jp|ke|kg|kh|ki|km|kn|kp|kr|kw|ky|kz|la|lb|lc|li|lk|lr|ls|lt|lu|lv|ly|ma|mc|md|me|mg|mh|mk|ml|mm|mn|mo|mp|mq|mr|ms|mt|mu|mv|mw|mx|my|mz|na|nc|ne|nf|ng|ni|nl|no|np|nr|nu|nz|om|pa|pe|pf|pg|ph|pk|pl|pm|pn|pr|ps|pt|pw|py|qa|re|ro|rs|ru|rw|sa|sb|sc|sd|se|sg|sh|si|s

y-tag

オンライン広告関連の文献

概要

オンライン広告まわりの研究へのポインタをいくつか。 以下のものから辿っていけばある程度は見つかるはず。

学会・ワークショップ

オンライン広告に関する論文は、国際学会では、ウェブ系・データマイニング系のWWW, WSDM, KDDや、情報検索系のSIGIR, CIKMあたりに出てくる印象。 後は、機械学習系のICMLやNIPSでもたまに出る。

yossale

var fs = require('fs');
var filePath = process.argv[2];

var content = null;

fs.readFile(filePath, 'utf8', function (err, data) {
    if (err) {
        console.log('Error: ' + err);
        return;
    }

rezoo

Caffe tutorial

この文章ではCNN実装であるCaffeを用いて，特徴ベクトルの抽出やパラメータの学習を行うための方法について説明する．

Caffeでサポートされている機能

以下の作業を行いたいのであれば，Caffeを用いることが望ましい．

• CNNを利用した画像の多クラス分類
• CNNによる特徴ベクトルの抽出
• CNNの転移学習
• Stacked Auto Encoder

mahmoud

import re

# the first group is noncapturing and just ensures we're at the beginning of 
# the string or have whitespace before the hashtag (don't want to capture anchors)
# without the fullwidth hashmark, hashtags in asian languages would be tough

hashtag_re = re.compile("(?:^|\s)[＃#]{1}(\w+)", re.UNICODE)