Guillaume Balaine Igosuki
| # 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 |
- 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
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
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
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.Html5historyinstead 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 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.
| """ | |
| 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 |
- 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