Satsuki Reikaa ReiiSky

The introduction to Reactive Programming you've been missing

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

Concurrency in JavaScript

Javascript is a programming language with a peculiar twist. Its event driven model means that nothing blocks and everything runs concurrently. This is not to be confused with the same type of concurrency as running in parallel on multiple cores. Javascript is single threaded so each program runs on a single core yet every line of code executes without waiting for anything to return. This sounds weird but it's true. If you want to have any type of sequential ordering you can use events, callbacks, or as of late promises.

Entities and Components

An entity is just a number.

There is a graph of components, indexed by the entity id.

All state is stored in one place.

var components = { Position: {}, Velocity:{}, Spite: {}, Timer: {}, ScreenShake: {}, RemoveComponents: {} }

Awesome Knowledge Graph Embedding Approaches

This list contains repositories of libraries and approaches for knowledge graph embeddings, which are vector representations of entities and relations in a multi-relational directed labelled graph. Licensed under CC0.

Libraries

Embedding framework (5 algorithms) @ https://github.com/BookmanHan/Embedding
KB2EP collection (5 algorithms) @ https://github.com/thunlp/KB2EP

	var express = require('express'),
	simpledb = require('simpledb'),
	Step = require('step'),

	sdb = new simpledb.SimpleDB({
	keyid: 'your aws key',
	secret: 'your aws secret'
	}),

	app = express.createServer(express.logger()),


	var net = require('net');

	// creates the server
	var server = net.createServer();

	//emitted when server closes ...not emitted until all connections closes.
	server.on('close',function(){
	console.log('Server closed !');
	});

	# -- coding: utf-8 --

	import sys
	import numpy

	numpy.seterr(all='ignore')


	'''

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

	'''
	Deep Belief Nets (DBN)

	References :
	- Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle: Greedy Layer-Wise
	Training of Deep Networks, Advances in Neural Information Processing
	Systems 19, 2007

	import gym
	import numpy as np

	env = gym.make('CartPole-v1')

	def play(env, policy):
	observation = env.reset()

	done = False
	score = 0

	setInterval(function(){
	document.getElementsByClassName('form-control')[0].value = document.getElementById('row1').getElementsByClassName('highlight')[0].innerHTML}, 100);