entaroadun

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:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

yefuchs

#The Great Firewall (GFW) Contributors List

注：数据来源为 dblp 和 cndblp, 下面括号中的数字表示 dblp 中显示的跟方滨兴合作论文的数量

###Binxing Fang (方滨兴)

中国工程院院士,北京邮电大学教授,中国科学院计算技术研究所网络方向首席科学家
http://en.wikipedia.org/wiki/Fang_Binxing

edufelipe

#include <string.h>
#include <stdio.h>
#include <unistd.h>
#include <ifaddrs.h>
#include <sys/types.h>
#include <sys/ioctl.h>
#include <sys/socket.h>
#include <linux/wireless.h>

raphw

import org.junit.Before;
import org.junit.Test;
import sun.misc.Unsafe;
import sun.reflect.ReflectionFactory;

import java.lang.reflect.Constructor;
import java.lang.reflect.Field;
import java.lang.reflect.Modifier;

import static org.junit.Assert.assertEquals;

Kartones

PSQL

Magic words:

psql -U postgres

Some interesting flags (to see all, use -h or --help depending on your psql version):

• -E: will describe the underlaying queries of the \ commands (cool for learning!)
• -l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)

stephenparish

Commit Message Conventions

These rules are adopted from the AngularJS commit conventions.

• Goals
• Generating CHANGELOG.md
  • Recognizing unimportant commits
  • Provide more information when browsing the history
• Format of the commit message
• Subject line

preshing

#! /bin/bash
set -e
trap 'previous_command=$this_command; this_command=$BASH_COMMAND' DEBUG
trap 'echo FAILED COMMAND: $previous_command' EXIT

#-------------------------------------------------------------------------------------------
# This script will download packages for, configure, build and install a GCC cross-compiler.
# Customize the variables (INSTALL_PATH, TARGET, etc.) to your liking before running.
# If you get an error and need to resume the script from some point in the middle,
# just delete/comment the preceding lines before running it again.

Spindel

Watchdogged

Place the service file (or a link to it) in /etc/systemd/system/ Place the watchdogged.py file somewhere ( and change the ExecStart portion in the .service to point at the file )

then do systemctl daemon-reload followed by systemctl start watchdogged.service

After this you can watch the progress using journalctl --follow -u watchdogged.service change the PROBABILITY variable to something else to watch it faster/later or succeed.

saliksyed

""" Deep Auto-Encoder implementation
	
	An auto-encoder works as follows:

	Data of dimension k is reduced to a lower dimension j using a matrix multiplication:
	softmax(W*x + b)  = x'
	
	where W is matrix from R^k --> R^j

	A reconstruction matrix W' maps back from R^j --> R^k

dain

# To regenerate the test key and certificates

# Generate an RSA private key and convert it to PKCS8 wraped in PEM
openssl genrsa 2048 | openssl pkcs8 -topk8 -inform pem -outform pem -nocrypt -out rsa.key
# Generate a certificate signing request with the private key
openssl req -new -key rsa.key -out rsa.csr
# Sign request with private key
openssl x509 -req -days 10000 -in rsa.csr -signkey rsa.key -out rsa.crt