Web Picks (week of 30 May 2016)

Every two weeks, we find the most interesting data science links from around the web and collect them in Data Science Briefings, the DataMiningApps newsletter. Subscribe now for free if you want to be the first to get up to speed on interesting resources.

  • Introducing our Hybrid lda2vec Algorithm
    “The goal of lda2vec is to make volumes of text useful to humans (not machines!) while still keeping the model simple to modify. It learns the powerful word representations in word2vec while jointly constructing human-interpretable LDA document representations.”
  • Unit testing in data science
    “An interesting topic we often hear data science organizations talk about is “unit testing.” It’s a longstanding best practice for building software, but it’s not quite clear what it really means for quantitative research work — let alone how to implement such a practice.”
  • Autoencoding Blade Runner
    “In this blog I detail the work I have been doing over the past year in getting artificial neural networks to reconstruct films — by training them to reconstruct individual frames from films, and then getting them to reconstruct every frame in a given film and resequencing it.”
  • Feed-forward neural doodle
    “What if you could only sketch the picture like a 3-years old and everything else is done by a computer so your sketch looks like a real painting? It will certainly happen in near future. In fact several algorithms that do the thing very well were proposed recently, yet they take at least several minutes to render your masterpiece using a high-end hardware. We make a step towards making such things available for everybody and present an online demo of our fast algorithm.”
  • One Chart, Twelve Charting Libraries
    “Charting Libraries. Gosh, there are so many out there. On Wikipedia and other websites, one can find a comparison of ca. 50 libraries – and these are only JavaScript libraries; not mentioning languages like Processing and libraries for Python and R. In the following blog post, I will try to get to know a few ones out of the great sea of possibilities. I want to understand their differences and how easy it is to learn them.”
  • Impatient R
    This is a tutorial for beginning to learn the R programming language, geared towards the impatient.