Web Picks (week of 19 October 2015)

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.

  • R vs Python: head to head data analysis
    There have been dozens of articles written comparing Python and R from a subjective standpoint, but this DataQuest article aims to look at the languages more objectively, showing what code is needed in both languages to achieve the same result: analyzing a small data set.
  • “Memory foam” approach to unsupervised learning
    The authors of this paper propose an alternative approach to construct an artificial learning system, which naturally learns in an unsupervised manner. Its mathematical prototype is a dynamical system, which automatically shapes its vector field in response to the input signal.
  • Hacking the Random Walk Hypothesis
    This article subjects various financial market returns to the NIST suite of tests to test the robustness of random number generators to see whether or not such market movements are in fact, equivalent to random walks.