jarutis

sudo su

# Java
yum -y install java-1.8.0-openjdk-devel

# Build Esentials (minimal)
yum -y install gcc gcc-c++ kernel-devel make automake autoconf swig git unzip libtool binutils

# Extra Packages for Enterprise Linux (EPEL) (for pip, zeromq3)
yum -y install epel-release

cloverstd

#!/usr/bin/env python
# encoding: utf-8

import tornado.ioloop
import tornado.web
import tornado.log
import tornado.httpserver
from tornado.options import define, options
import logging
import tornado.gen

ntamvl

Upstart script for DeepDetect

Create upstart config /etc/init/deepdetect.conf

description "DeepDetect"

start on filesystem or runlevel [2345]
stop on run level [!2345]

indrayam

Pseudocode:

Y = Base64URLEncode(Header) + ‘.’ + Base64URLEncode(Payload)
JWT = Y + ‘.’ + Base64URLEncode(HMACSHA256(Y))

The steps called out here should work on a Mac as well. The only thing that might be different is the sed command used below. Instead of using -E, you will have to use -r to run sed with extended regular expression support

Use data from this tutorial:

scotch.io

kracekumar

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

import asyncio
import uvloop
from aiohttp.web import Application, MsgType, WebSocketResponse


def add_socket(app, socket, user_id):
    if user_id in app['connections']:
        pass

GilLevi

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Convolutional neural networks for emotion classification from facial images as described in the following work:

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015

Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/

If you find our models useful, please add suitable reference to our paper in your work.

genekogan

Instructions for making a Neural-Style movie

The following instructions are for creating your own animations using the style transfer technique described by Gatys, Ecker, and Bethge, and implemented by Justin Johnson. To see an example of such an animation, see this video of Alice in Wonderland re-styled by 17 paintings.

Setting up the environment

The easiest way to set up the environment is to simply load Samim's a pre-built Terminal.com snap or use another cloud service like Amazon EC2. Unfortunately the g2.2xlarge GPU instances cost $0.99 per hour, and depending on parameters selected, it may take 10-15 minutes to produce a 512px-wide image, so it can cost $2-3 to generate 1 sec of video at 12fps.

If you do load the

harlow

Golang Workers / Job Queue

A running example of the code from:

• http://marcio.io/2015/07/handling-1-million-requests-per-minute-with-golang
• http://nesv.github.io/golang/2014/02/25/worker-queues-in-go.html

This gist creates a working example from blog post, and a alternate example using simple worker pool.

TLDR: if you want simple and controlled concurrency use a worker pool.

protrolium

ffmpeg

Converting Audio into Different Formats / Sample Rates

Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma

You can get the list of supported formats with:
ffmpeg -formats

You can get the list of installed codecs with:

jorinvo

You got your hands on some data that was leaked from a social network and you want to help the poor people.

Luckily you know a government service to automatically block a list of credit cards.

The service is a little old school though and you have to upload a CSV file in the exact format. The upload fails if the CSV file contains invalid data.

The CSV files should have two columns, Name and Credit Card. Also, it must be named after the following pattern:

YYYYMMDD.csv.