Web Picks (week of 13 February 2017)

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.

  • Hans Rosling: An Appreciation
    Two weeks ago, the world lost Hans Rosling, a data visionary whose TED Talk, The Best Stats You’ve Ever Seen, quickly became a classic in 2006 and has since had more than 11 million views. This post by Robert Kosara highlights Rosling’s achievements and includes links to key talks and projects.
  • Introduction to Anomaly Detection
    This overview will cover several methods of detecting anomalies, as well as how to build a detector using simple moving average (SMA) or low-pass filter.
  • U.S. Open Data is currently Closed…
    In 2013, President Obama signed an executive order that made open and machine-readable data the new default for U.S. government information. It was one of Obama’s hallmark achievements and led to several initiatives to scale up the accessibility of data across government sectors. As has been widely reported this week, Open Data appears to be Closed.
  • Deep Learning for Chess
    “I’ve been meaning to learn Theano for a while and I’ve also wanted to build a chess AI at some point. So why not combine the two?”
  • Building Applications With Deep Learning: Expectations vs. Reality
    Nowadays, building applications involves many technologies. There are technologies to render user interfaces, to retrieve and store data, to serve many users, to distribute computing, etc. Increasingly, certain requirements imply the usage of neural networks. So what is the reality of building enterprise applications with the available state-of-the-art neural network technology?
  • R Tutorial: Visualizing multivariate relationships in Large Datasets
    “In two previous blog posts I discussed some techniques for visualizing relationships involving two or three variables and a large number of cases. In this tutorial I will extend that discussion to show some techniques that can be used on large datasets and complex multivariate relationships involving three or more variables.”
  • Deep Learning in R
    This blog entry aims to provide an overview and comparison of different deep learning packages available for the programming language R.
  • Building a deep learning DOOM bot
    Fun read: this article is the first in a series of posts that will focus on an exploratory journey of reinforcement based Deep Learning utilizing the VizDoom platform.
  • Using Machine Learning to predict parking difficulty
    “Much of driving is spent either stuck in traffic or looking for parking. With products like Google Maps and Waze, it is our long-standing goal to help people navigate the roads easily and efficiently. But until now, there wasn’t a tool to address the all-too-common parking woes.”
  • Intro to Data Science for Academics
    Data science is a good match for many former academics because it leverages some of the math and statistics knowledge that many PhDs learn and use.
  • Color quantization using k-means
    Color quantization is the process of reducing the number of distinct colors used in an image. The main reason we may want to perform this kind of compression is to enable the rendering of an image in devices supporting only a limited number of colors (usually due to memory limitations).