(by @andrestaltz)
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.
| This playbook has been removed as it is now very outdated. |
| import java.io.*; | |
| import java.util.*; | |
| /** The class encapsulates an implementation of the Apriori algorithm | |
| * to compute frequent itemsets. | |
| * | |
| * Datasets contains integers (>=0) separated by spaces, one transaction by line, e.g. | |
| * 1 2 3 | |
| * 0 9 | |
| * 1 9 |
| # Install dependencies | |
| # | |
| # * checkinstall: package the .deb | |
| # * libpcre3, libpcre3-dev: required for HTTP rewrite module | |
| # * zlib1g zlib1g-dbg zlib1g-dev: required for HTTP gzip module | |
| apt-get install checkinstall libpcre3 libpcre3-dev zlib1g zlib1g-dbg zlib1g-dev && \ | |
| mkdir -p ~/sources/ && \ | |
| # Compile against OpenSSL to enable NPN |
(by @andrestaltz)
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.
| import theano | |
| import theano.tensor as T | |
| from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams | |
| from theano.tensor.signal.downsample import max_pool_2d | |
| from theano.tensor.extra_ops import repeat | |
| from theano.sandbox.cuda.dnn import dnn_conv | |
| from time import time | |
| import numpy as np | |
| from matplotlib import pyplot as plt |
This gist is an implementation of http://sirile.github.io/2015/05/18/using-haproxy-and-consul-for-dynamic-service-discovery-on-docker.html on top of Docker Machine and Docker Swarm.
| // Hook in to `addEventListener` to track the mouse and display it as a circle | |
| exports.onPageLoad = function() { | |
| return browser.executeScript(function() { | |
| (function() { | |
| var EventSniffer = function() { | |
| this.history = []; | |
| this.callbacks = {}; | |
| this.minCacheSize = 100; | |
| this.maxCacheSize = 500; | |
| }; |