- Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
- Models and Issues in Data Stream Systems
- Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
- Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
- [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
(function() { | |
var CSSCriticalPath = function(w, d, opts) { | |
var opt = opts || {}; | |
var css = {}; | |
var pushCSS = function(r) { | |
if(!!css[r.selectorText] === false) css[r.selectorText] = {}; | |
var styles = r.style.cssText.split(/;(?![A-Za-z0-9])/); | |
for(var i = 0; i < styles.length; i++) { | |
if(!!styles[i] === false) continue; | |
var pair = styles[i].split(": "); |
""" | |
A deep neural network with or w/o dropout in one file. | |
License: Do What The Fuck You Want to Public License http://www.wtfpl.net/ | |
""" | |
import numpy, theano, sys, math | |
from theano import tensor as T | |
from theano import shared | |
from theano.tensor.shared_randomstreams import RandomStreams |
This is my response to an email asking about Domain-Driven Design in golang project.
Thank you for getting in touch. Below you will find my thoughts on how golang works with DDD, changing it. This is merely a perception of how things worked out for us in a single project.
That project has a relatively well-known domain. My colleagues on this project are very knowledgeable, thoughtful and invested in quality design. The story spelled out below is a result of countless hours spent discussing and refining the approach.
Conclusions could be very different, if there was a different project, team or a story-teller.
This is the example that comes with the reagent template converted to use HTML5 based history. This means there are no #
in the urls.
I just got this working, so there might be better approaches
The changes are
- use
goog.history.Html5history
instead ofgoog.History
- listen to clicks on the page, extract the path from them, and push them onto the history
- listen to history changes, and have secretary do its thing in response
This cheat sheet originated from the forum, credits to Laurent Poulain. We copied it and changed or added a few things.
- Call by value: evaluates the function arguments before calling the function
- Call by name: evaluates the function first, and then evaluates the arguments if need be
def example = 2 // evaluated when called
val example = 2 // evaluated immediately
Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.
This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would
- Re-frisk Visualize re-frame pattern data or reagent ratom data as a tree structure, watch re-frame events and export state in the debugger
- Dirac A Chrome DevTools fork for ClojureScript developers
- BinaryAge custom formatters for ClojureScript
# REFERENCES: | |
# - https://github.com/puckel/docker-airflow | |
# - https://github.com/ImDarrenG/mesos-framework-dev/blob/master/Dockerfile | |
# - https://github.com/Stibbons/docker-airflow-mesos | |
# Wherever you store your mesos image built from Dockerfile-mesos | |
FROM slicelife/mesos:1.4.0 as mesos | |
FROM ubuntu:16.04 | |
# Never prompts the user for choices on installation/configuration of packages | |
ENV DEBIAN_FRONTEND noninteractive |