dideler

The program below can take one or more plain text files as input. It works with python2 and python3.

Let's say we have two files that may contain email addresses:

1. file_a.txt

foo bar
ok [email protected] sup
 [email protected],wyd
hello world!

andris9

Setup reverse tunnel

Run the following in your client machine

ssh -R EXPOSED_PORT:localhost:SERVICE_PORT USER@HOST

Where

• EXPOSED_PORT is the port exposed to the internet in the proxy server
• SERVICE_PORT is the port your application is listening in your machine

kastnerkyle

# (C) Kyle Kastner, June 2014
# License: BSD 3 clause

import numpy as np
from scipy import sparse


def minibatch_indices(X, minibatch_size):
    minibatch_indices = np.arange(0, len(X), minibatch_size)
    minibatch_indices = np.asarray(list(minibatch_indices) + [len(X)])

iksose

###Creating a REST API using Node.js, Express, and MongoDB

####Installing Node.js

Go to http://nodejs.org, and click the Install button. Run the installer that you just downloaded. When the installer completes, a message indicates that Node was installed at /usr/local/bin/node and npm was installed at /usr/local/bin/npm. At this point node.js is ready to use. Let’s implement the webserver application from the nodejs.org home page. We will use it as a starting point for our project: a RESTful API to access data (retrieve, create, update, delete) in a wine cellar database.

Create a folder named nodecellar anywhere on your file system. In the wincellar folder, create a file named server.js.

dweinstein

Source: http://christonard.com/12-free-data-mining-books/

• An Introduction to Statistical Learning with Applications in R by James, Witten, Hastie & Tibshirani – This book is fantastic and has helped me quite a bit. It provides an overview of several methods, along with the R code for how to complete them. 426 Pages.
• The Elements of Statistical Learning by Hastie, Tibshirani & Friedman – This is an in-depth overview of methods, complete with theory, derivations & code. I’d definitely consider this a graduate level text. I’d also consider it one of the best books available on the topic of data mining. 745 Pages.
• A Programmer’s Guide to Data Mining by Ron Zacharski – This one is an online book, each chapter downloadable as a PDF. It’s also still in progress, with chapters being added a few times each year. Probabilistic Programming & Bayesian Methods for Hackers by Cam Davidson-Pilson – This book is absolutely fantastic. The author explains Bayesian statistics, provides several diverse examples of how to a

NV

var app = angular.module('converter', []);

app.controller('MainController', function($scope) {
	$scope.a = 0;
});

app.directive('converter', function(converters) {
	return {
		require: 'ngModel',
		link: function(scope, element, attr, ngModel) {

prakhar1989

Rich Hickey on becoming a better developer

Rich Hickey • 3 years ago

Sorry, I have to disagree with the entire premise here.

A wide variety of experiences might lead to well-roundedness, but not to greatness, nor even goodness. By constantly switching from one thing to another you are always reaching above your comfort zone, yes, but doing so by resetting your skill and knowledge level to zero.

Mastery comes from a combination of at least several of the following:

miloharper

from numpy import exp, array, random, dot
training_set_inputs = array([[0, 0, 1], [1, 1, 1], [1, 0, 1], [0, 1, 1]])
training_set_outputs = array([[0, 1, 1, 0]]).T
random.seed(1)
synaptic_weights = 2 * random.random((3, 1)) - 1
for iteration in xrange(10000):
    output = 1 / (1 + exp(-(dot(training_set_inputs, synaptic_weights))))
    synaptic_weights += dot(training_set_inputs.T, (training_set_outputs - output) * output * (1 - output))
print 1 / (1 + exp(-(dot(array([1, 0, 0]), synaptic_weights))))

shagunsodhani

Efficient Estimation of Word Representations in Vector Space

Introduction

• Introduces techniques to learn word vectors from large text datasets.
• Can be used to find similar words (semantically, syntactically, etc).
• Link to the paper
• Link to open source implementation

Model Architecture

dannguyen

Using Selenium and Python to screenshot a javascript-heavy page

As websites become more JavaScript heavy, it's harder to automate things like screenshotting for archival purposes. I've seen examples and suggestions to use PhantomJS for visual testing/archiving of websites, but have run into issues such as the non-rendering of webfonts. I've never tried out Selenium until today...and while I'm not thinking about performance implications yet, Selenium seems far more accurate than PhantomJS...which makes sense since it actually opens a real browser. And it's not too hard to script to do complex interactions: here's an [example of how to log in to Twitter, write a tweet, upload an image, and send a tweet via Selenium and DOM element selection](https://gist.github.com/dannguyen/8a6fa49253c1d6a0eb92