mnpappo’s gists

mnpappo / prothom_alo_article_scrab.py

Created June 22, 2018 15:51

	# encoding=utf8
	import sys
	reload(sys)
	sys.setdefaultencoding('utf8')

	import urllib
	import csv
	import os
	from datetime import date, timedelta
	from bs4 import BeautifulSoup

mnpappo / fbapp.php

Created November 26, 2017 07:14

	# index.php

	<?php

	session_start();
	require_once __DIR__ . '/vendor/autoload.php';
	$fb = new Facebook\Facebook([
	'app_id' => '143450773085054',
	'app_secret' => 'df5a3ec54d85f3ffe68c3709ceaccce9 ',
	'default_graph_version' => 'v2.11',

mnpappo / index.html

Last active October 27, 2017 19:01

	<!DOCTYPE html>
	<html>

	<head>
	<title>Facebook Login JavaScript Example</title>
	<link rel="stylesheet" href="https://bootswatch.com/cyborg/bootstrap.min.css">
	<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
	<style media="screen">
	#fb-btn { margin-top: 20px;
	}

mnpappo / classifier_from_little_data_script_1.py

Created October 23, 2017 21:33 — forked from fchollet/classifier_from_little_data_script_1.py

Updated to the Keras 2.0 API.

	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.
	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data
	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	- created cats/ and dogs/ subfolders inside train/ and validation/
	- put the cat pictures index 0-999 in data/train/cats

mnpappo / fb login api

Created October 17, 2017 11:45

	<!DOCTYPE html>
	<html>

	<head>
	<title>Facebook Login JavaScript Example</title>
	<meta charset="UTF-8">
	</head>

	<body>
	<script>

mnpappo / latex image

Last active August 5, 2017 05:27

	\usepackage{graphicx, wrapfig}
	\usepackage{rotating}
	\usepackage{subfig}
	\graphicspath{ {resource/} }


	\begin{figure}[!hb]
	\includegraphics[width=0.8\textwidth]{mlp-ann.png}
	\centering
	\caption{Multi-Layer Perceptron}

mnpappo / min-char-rnn.py

Created April 19, 2017 01:53 — forked from karpathy/min-char-rnn.py

Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy

	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)

mnpappo / Aircrack Commands

Created February 24, 2017 15:45 — forked from victorreyesh/Aircrack Commands

Cracking WPA2 / WEP Wifi / Aircrack 10 seconds guide. For Mac OSX

	//Install Macports.
	//Install aircrack-ng:
	sudo port install aircrack-ng
	//Install the latest Xcode, with the Command Line Tools.
	//Create the following symlink:
	sudo ln -s /System/Library/PrivateFrameworks/Apple80211.framework/Versions/Current/Resources/airport /usr/sbin/airport
	//Figure out which channel you need to sniff:
	sudo airport -s

	sudo airport en1 sniff [CHANNEL]

mnpappo / last 7 days posts

Created January 10, 2016 12:06

mnpappo / relay.py

Created December 22, 2015 21:33

	from flask import Flask, render_template
	from gpiozero import LED
	import RPi.GPIO as GPIO
	import time

	led1 = LED(4)
	# init list with pin numbers
	pinList = [2, 3]
	# time to sleep between operations in the main loop
	SleepTimeL = 2

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