Weekly Round-Up: Probabilistic Programming, Tech Startups, Data Viz Elements, and Super Mario Bros.

Welcome back to the round-up, an overview of the most interesting data science, statistics, and analytics articles of the past week. This week, we have 4 fascinating articles ranging in topics from probabilistic programming to machines playing video games. In this week's round-up:

  • What is Probabilistic Programming?
  • 5 Ways for Tech Start-Ups to Attract Analytics Talent
  • The Three Elements of Successful Data Visualizations
  • AI Solves Super Mario Bros and Other NES Games

What is Probabilistic Programming?

This is an interesting O'Reilly article introducing probabilistic programming. The article talks about what probabilistic programming is, how it differs from regular high-level programming, and intuitively explains how it works. The author also explains how he believes the technology's development will progress and the impact it will have on data science and other technologies.

5 Ways for Tech Start-Ups to Attract Analytics Talent

For those looking to hire analytical talent, this article provides some practical pointers for hiring a data scientist. These pointers focus on some of the softer skills that are necessary to really excel in these types of roles and also on structuring an environment where your data scientists are properly motivated to do their absolute best work.

The Three Elements of Successful Data Visualizations

This is a Harvard Business Review article about what elements are necessary in making great data visualizations. The article highlights three elements - understanding the audience, setting up and framework, and telling a story - and explains why each of these are important in a little more detail.

AI Solves Super Mario Bros and Other NES Games

This article is about an interesting and fun application of machine learning - teaching a machine to solve video games. It revolves around a paper written by computer scientist Tom Murphy about how he was able to accomplish this using lexicographic ordering. The article talks about Murphy's research and how he went about figuring out how to do this. It also has a link to Murphy's paper for those that would like some more in-depth reading on the subject.

That's it for this week. Make sure to come back next week when we’ll have some more interesting articles! If there's something we missed, feel free to let us know in the comments below.

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