Data Science Weekly Newsletter - Issue 97

Issue #97

October 1 2015

Editor Picks
  • The Internet Knows If You’ll Be Dead
    These authors used three years of electronic health record data to derive a predictive Bayesian network for patient status. Its scope: home, hospitalized, or dead. There are many simple models for predicting such things, but this one is interesting because it attempts to utilize multiple patient features, vital signs, and laboratory results in a continuously updating algorithm. Ultimately, their model was capable of predicting outcomes up through one week from the initial hospitalization event...
  • Google DeepMind Artificial Intelligence can beat Humans at 31 video games but can't master Pac-Man
    Google-owned artificial intelligence start-up DeepMind has revealed that its deep learning software is now able to outperform humans in 31 different video games. The algorithm, which uses reinforcement learning to master the games, has been described as the "first significant rung of the ladder" towards proving such a system can work, and a significant step towards use in real-world applications...
  • Classifying Steps with Machine Learning at Jawbone
    When we first began to explore the idea of building a step classifier, we knew we would be constrained to a very limited population of individuals (Jawbone employees) available to us for early development and testing...

A Message from this week's Sponsor:



Data Science Articles & Videos

  • Liberty Mutual Property Inspection, Winner's Interview: Qingchen Wang
    The hugely popular Liberty Mutual Group: Property Inspection Prediction competition wrapped up on August 28, 2015 with Qingchen Wang at the top of a crowded leaderboard. A total of 2,362 players on 2,236 teams competed to predict how many hazards a property inspector would count during a home inspection...
  • Optimizing RNN performance
    This is part I of a multi-part series detailing some of the techniques we've used here at Baidu's Silicon Valley AI Lab to accelerate the training of recurrent neural networks. This part focuses on GEMM performance...
  • Statistics Without the Agonizing Pain
    There are two essential skills for the data scientist: engineering and statistics. A great many data scientists are very strong engineers but feel like impostors when it comes to statistics. In this talk John will argue that the ability to program a computer gives you special access to the deepest and most fundamental ideas in statistics. John’s goal is to convince the non-statistician engineers in the audience that the road to statistical fluency is much, much shorter than they think...
  • Google voice search: faster and more accurate
    Today, we’re happy to announce we built even better neural network acoustic models using Connectionist Temporal Classification (CTC) and sequence discriminative training techniques. These models are a special extension of recurrent neural networks (RNNs) that are more accurate, especially in noisy environments, and they are blazingly fast!...
  • The sorry state of football analytics
    The sad truth of the matter is that the state of football analytics in 2015 is not good and isn't showing signs of improving. This is especially true in the NFL, though I think a lot of this applies to college football as well. The body of football research is not advancing with the same rate and is not of the same quality as in basketball, baseball, or hockey...


  • VP Data Science - The Weather Company - NYC

    We are The Weather Company, and our name speaks for itself. We are a company focused entirely on the weather,and we’re proud to say we reach two-thirds of all U.S. adults through a media portfolio that includes The Weather Channel, and our mobile applications –Weather Services International, and Weather Underground. The VP of Data Science will lead a team of data scientists, engineers, and product managers working on massive sets of weather, location, and audience data. The VP will define data science strategy across all of our advertising products, and own building and implementing proprietary methods in the areas of audience targeting, ad attribution, mobile and location-based targeting, and performance tracking across all of our ad products. ...

Training & Resources

  • How do neural networks learn?
    To help understand how neural networks learn, I built a visualization of a network at the neuron level, including animations that show how it learns...



  • The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

    New release...

    "With terms like ‘Machine Learning’ and ‘Big Data’ regularly making headlines, there is no shortage of hype-filled business books on the subject. There are also textbooks that are too technical to be accessible. For those in the middle—from executives to college students—this is the ideal book, showing how and why things really work without the heavy math..."

    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
P.S. Interested in reaching fellow readers of this newsletter? Consider sponsoring! Email us for details :) - All the best, Hannah & Sebastian
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