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Data Science Weekly Newsletter
June 16, 2016

Editor's Picks

  • Teaching Robots to Feel: Emoji & Deep Learning
    Recently, neural networks have become the tool of choice for a variety of tough computer-science problems: Facebook uses them to identify faces in photos, Google uses them to identify everything in photos. Apple uses them to figure out what you’re saying to Siri, and IBM uses them for operationalizing business unit synergies. It’s all very impressive. But what about the real problems? Can neural networks help you find the emoji when you really need it?...
  • Ten Simple Rules for Effective Statistical Practice
    Several months ago, Phil Bourne, the initiator and frequent author of the wildly successful and incredibly useful “Ten Simple Rules” series, suggested that some statisticians put together a Ten Simple Rules article related to statistics...

A Message From This Week's Sponsor

  • “The Science of Data-Driven Storytelling”

    DataScience Inc. and the National Science Foundation’s West Big Data Innovation Hub have brought together leaders in academia, the non-profit sector, government, data science and publishing to discuss best practices for creating impactful data-driven stories. Click here to register
    for the live-streamed workshop, “The Science of Data-Driven Storytelling”.

Data Science Articles & Videos

  • AI, Deep Learning, and Machine Learning: A Primer
    Things are clearly progressing rapidly when it comes to machine intelligence. But how did we get here, after not one but multiple “A.I. winters”? What’s the breakthrough? And why is Silicon Valley buzzing about artificial intelligence again? From types of machine intelligence to a tour of algorithms, a16z Deal and Research team head Frank Chen walks us through the basics (and beyond) of AI and deep learning in this slide presentation....
  • MicrobeSifter: mapping complex microbe genomics samples using NLP
    While the cost of DNA sequencing continues to plummet, the data being generated is increasingly complex. A single environmental sample containing hundreds or thousands of different organisms can be sequenced to determine the relative abundance of each organism present. The ability to reproducibly deliver results that are both accurate and sensitive is paramount...
  • R Passes SAS in Scholarly Use (finally)
    Way back in 2012 I published a forecast that showed that the use of R for scholarly publications would likely pass the use of SAS in 2015. But I didn’t believe the forecast since I expected the sharp decline in SAS and SPSS use to level off. I just collected data on the most recent complete year of scholarly publications, and it turns out that 2015 was indeed the year that R passed SAS to garner the #2 position...
  • Twitter Sentiment Analysis for Finance/Trading
    Metricle is a big data analytics company that provides actionable financial alerts in real-time. The company's proprietary algorithms curate Twitter, SEC filings, major wires, price feeds, blogs, chat rooms, and news outlets, transforming hundreds of gigabytes of data into actionable alerts, focusing on both early event detection and sentiment analysis...


  • NLP Data Scientist - - New York is building a virtual personal assistant based on natural language understanding (NLP) and dialogue modeling. Our start-up began 2 years ago and we have successfully gone through $23M round-B funding. We have an awesome dataset, an awesome team of data scientists and an equally awesome NLP challenge...

Training & Resources

  • High-level Learn Module in TensorFlow
    In this post, I will explain some major changes introduced since v0.9 to help existing users understand the code better as well as a call for contributors for this exciting and rapid growing project...


  • Data Scientists At Work A collection of interviews with sixteen of the world's most influential and innovative data scientists...

    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page...

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