Luis lfcunha

Movies Recommendation:

MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

How to setup Let's Encrypt for Nginx on Ubuntu 16.04 (including IPv6, HTTP/2 and A+ SLL rating)

There are two main modes to run the Let's Encrypt client (called Certbot):

Webroot is better because it doesn't need to replace Nginx (to bind to port 80).

In the following, we're setting up mydomain.com. HTML is served from /var/www/mydomain, and challenges are served from /var/www/letsencrypt.

	from numpy import loadtxt, zeros, ones, array, linspace, logspace
	from pylab import scatter, show, title, xlabel, ylabel, plot, contour


	#Evaluate the linear regression
	def compute_cost(X, y, theta):
	'''
	Comput cost for linear regression
	'''
	#Number of training samples

	from numpy import loadtxt, zeros, ones, array, linspace, logspace, mean, std, arange
	from mpl_toolkits.mplot3d import Axes3D
	import matplotlib.pyplot as plt
	from pylab import plot, show, xlabel, ylabel

	#Evaluate the linear regression

	def feature_normalize(X):
	'''
	Returns a normalized version of X where