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Data Science Weekly Newsletter
Issue
34
July 17, 2014

Editor's Picks

  • Why Probabilistic Programming Matters
    Last week, DARPA announced a new program to fund research in probabilistic programming languages. While the accompanying news stories gave a certain angle on why this was important, this is a new research area and it's still pretty mysterious to most people who care about machine intelligence. So: what is probabilistic programming, and why does it matter?...



Data Science Articles & Videos

  • Understanding Convolutions
    In a previous post, we built up an understanding of convolutional neural networks, without referring to any significant mathematics. To go further, however, we need to understand convolutions...
  • Stastical Advice for A/B Testing
    A/B testing is awesome. It's fun, it's lucrative, and it's one of the most visible and impactful things that you can do as a data scientist / statistician / anyone-interested-in-optimization at a company. Unfortunately, good statistical methods for A/B testing are more complicated then they are sometimes thought to be...
  • What is deep learning, and why should you care?
    I’ve never encountered such a big improvement from a technique [Deep Learning] that was largely unheard of just a couple of years before, so I became obsessed with understanding more. To be able to use it commercially across hundreds of millions of photos, I built my own specialized library to efficiently run prediction on clusters of low-end machines and embedded devices, and I also spent months learning the dark arts of training neural networks. Now I’m keen to share some of what I’ve found...
  • Complementary Approaches to Forecasting Political Events
    Advances in technology and the popularity of individuals like Nate Silver have given rise to the exciting idea that political scientists can predict the future using statistical models. Despite the recent attention forecasting has received, it is still difficult to do well, especially for rare political events like the onset of mass atrocities. In order to address this challenge, the Early Warning Project has developed a system that combines statistical forecasting with crowd-sourced forecasts...
  • Music Recommendations with 300M Data Points and one SQL Query
    While toying with the public BigQuery datasets, impatiently waiting for Google Cloud Dataflow to be released, I’ve noticed the Wikipedia Revision History one, which contains a list of 314M Wikipedia edits, up to 2010. In the spirit of Amazon’s “people who bought this”, I’ve decided to run a small experiment about music recommendations based on Wikipedia edits. The results are not perfect, but provide some insights that could be used to bootstrap a recommendation platform...



Jobs

  • Data Scientist - Shutterstock - New York, NY
    As a Data Scientist, you will be joining the team responsible for pushing technology boundaries in areas such as language translation, image recognition, natural language processing, and search ranking. Your work will directly empower the Shutterstock customer experience seen by millions of customers daily, and will enable new and unique customer features that drive Shutterstock's best in-class image and video search engine...


Training & Resources

  • 8 great data blogs to follow
    Below I've listed my favourite data analysis, data science, or otherwise technical blogs that I've learned a great deal from...


Books



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