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Data Science Weekly Newsletter
January 29, 2015

Editor's Picks

  • Providence: Machine Learning At Stack Exchange
    At Stack Exchange, we’ve historically been pretty loose with our data analysis. You can see this in the “answered questions” definition (has an accepted answer or an answer with score > 0), “question quality” (measured by ad hoc heuristics based on votes, length, and character classes), “interesting tab” homepage algorithm (backed by a series of experimentally determined weights), and rather naïve question search function. But as our community grows and we tackle more difficult problems we’ve needed to become more sophisticated...
  • How to Hire Your First Data Scientist
    Given the rise in the popularity of Data Science as of late, one only needs to be on recruiter mailing lists, look at company openings, or comb through Linkedin or Indeed's job postings to see that the Data Scientist position comes in a multitude of forms, some true to the name, some simply a Business Analyst in disguise. I remain unconvinced that the majority of employers clearly understand what a Data Scientist is, does, or how they can even help. With that, the purpose of this post is help guide employers and hiring managers looking to add a Data Scientist to their team...
  • Comments on Warren Sharp's Patriots Fumble Analysis
    First, an admission. I am a life-long New England Patriots fan. You could probably assume that because there is no other reason I would put the time into this analysis that I have. On the other hand, I definitely value good statistical analyses leading to well-founded conclusions that elucidate difficult concepts for people instead of adding more confusion...

Data Science Articles & Videos

  • Why now is the time to learn R
    With such strong demand and such high salaries to offer, it’s no surprise that competition for hiring data scientists is intense. As a result, companies who previously relied on legacy proprietary platforms for statistical analysis are now adopting a new alternative, open source R. So far, it has been chosen by more than two million data scientists and statisticians around the world...
  • Building A Data Science Portfolio Project Top Down
    Having a data science portfolio which showcases your skills in the areas your future employer wants is a great way to get the data science job of your dreams. This article will cover the basics of the top down approach - starting with questions...
  • Twitter Mapping: Twitter’s Data Editor Highlights Challenges & Possibilities
    With more than 500 million tweets sent every day, Twitter data as a whole can seem huge and unimaginable, like cramming the contents of the Library of Congress into your living room. One way of trying to make that big data understandable is by making it smaller and easier to handle by giving it context; by putting it on a map...
  • Jawbone: Weight Loss - What Really Works
    This week, as millions of people try to keep their New Year resolutions past the month of January, we decided to dig into our rich data set to answer a simple question: What are the most effective ways to lose weight?...
  • How racial discrimination in law enforcement actually works
    You see it all the time in studies. "We controlled for..." And then the list starts. The longer the better. Income. Age. Race. Religion. Height. Hair color. Sexual preference. Crossfit attendance. Love of parents. Coke or Pepsi. The more things you can control for, the stronger your study is — or, at least, the stronger your study seems...


  • Data Scientist - New York Times - NYC
    The New York Times is a technology company committed to producing the world's most reliable and highest quality journalism. Our ability to do so relies on a growing, talented team of expert technologists who learn from a tremendous abundance of data unique to this company. As well-documented in the 2014 New York Times Innovation Report, a core function of learning from our data is "the art and science" of understanding and developing our audience, particularly across new digital platforms and products. The Times seeks a Data Scientist to join a growing Data Science Group applying machine learning methods to meet this challenge, in close collaboration with working partners in the newsroom....

Training & Resources

  • Deep Learning University - Archive Update
    It has been a while (November 2014) since our last update to the deeplearning bibliography at – but underneath is an update with 408 recent papers...
  • Awesome AI
    A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers...


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