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Data Science Weekly Newsletter
July 11, 2019

Editor's Picks

  • This New Poker Bot Can Beat Multiple Pros—at Once
    Darren Elias knows poker. The 32-year-old is the only person to have won four World Poker Tour titles and has earned more than $7 million at tournaments. Despite his expertise, he learned something new this spring from an artificial intelligence bot...
  • Role of a Data Science Manager
    A series on effective Data Science Management by Sequoia. This first article describes the functions served by an effective DS manager and dives into the two most important responsibilities of a data science leader: driving impact and building a world class team...

A Message From This Week's Sponsor

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Data Science Articles & Videos

  • Who’s Listening When You Talk to Your Google Assistant?
    Google, Amazon and Apple say their AI-powered virtual assistants make it easier to get things done on smartphones or at home. Last month, a couple in the Waasmunster area of Belgium got an unexpected lesson in how these supposedly automated helpers really work...
  • Cloud TPU Pods break AI training records
    Google Cloud’s AI-optimized infrastructure makes it possible for businesses to train state-of-the-art machine learning models faster, at greater scale, and at lower cost. These advantages enabled Google Cloud Platform (GCP) to set three new performance records in the latest round of the MLPerf benchmark competition, the industry-wide standard for measuring ML performance...
  • Predicting the Generalization Gap in Deep Neural Networks
    We propose the use of a normalized margin distribution across network layers as a predictor of the generalization gap. We empirically study the relationship between the margin distribution and generalization and show that, after proper normalization of the distances, some basic statistics of the margin distributions can accurately predict the generalization gap. We also make available all the models used as a dataset for studying generalization through the Github repository...
  • San Francisco hopes AI will prevent bias in prosecutions
    San Francisco will soon implement AI in a bid to prevent bias when prosecuting a potential criminal. Even subconscious human biases can impact courtroom decisions. Racial bias in the legal system is particularly well-documented (PDF) and often leads to individuals with darker skin being prosecuted more, or with tougher sentencing, than people with lighter skin tones accused of similar crimes. To combat this, San Francisco will use a ‘bias mitigation tool’ which automatically redacts any information from a police report that could identify a suspect’s race...
  • How to plan and execute your ML and DL projects
    This article is the first one in a series that will be dedicated to forming a path for channelling out deep learning projects in a holistic manner. We will start off by discussing the importance of having a good strategy to structure deep learning projects. We will then decompose the units that are responsible for developing a deep learning project at a production scale and study the first set of units...
  • Simulacra And Selection
    Recommendation tutorials often cover matrix factorization. In practice, there are more business constraints to satisfy. For example, instead of predicting clothes a user will like, can you recommend a whole outfit?. StitchFix share their algorithmic approach...
  • Real-time Hair segmentation and recoloring on Mobile GPUs
    We present a novel approach for neural network-based hair segmentation from a single camera input specifically designed for real-time, mobile application. Our relatively small neural network produces a high-quality hair segmentation mask that is well suited for AR effects, e.g. virtual hair recoloring...
  • Fast Universal Style Transfer for Artistic and Photorealistic Rendering
    While existing methods typically need multiple rounds of time-consuming AE reconstruction for better stylization, our work intends to design novel neural network architectures on top of AE for fast style transfer with fewer artifacts and distortions all in one pass of end-to-end inference. To this end, we propose two network architectures named ArtNet and PhotoNet to improve artistic and photo-realistic stylization, respectively...


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  • Senior Data Scientist - TRANZACT - NJ or Raleigh, NC

    Tranzact is a fast paced, entrepreneurial company offering a well-rounded suite of marketing solutions to help insurance companies stay ahead of the competition. The Senior Data Scientist will be solving the toughest problems at Tranzact by using data. More specifically, responsible for gathering data, conducting analysis, building predictive algorithms and communicating findings to drive profitable growth and performance across Tranzact. Must have a strong grasp on the data structure, business needs, and statistical and predictive modeling. Minimum 7 years of experience building predictive algorithms...
        Want to post a job here? Email us for details >>

Training & Resources

  • Six Steps To Take Before Pursuing Education To Get A Data Science Job
    Do you find yourself thinking I'm a bit of an unlikely candidate to do Data Science because I don't have a PhD in Computer Science or Mathematics? Do you feel like almost all of the companies hiring Data Scientists are looking for people with advanced degrees, so you find yourself wondering if you should go through 5-6 years in a PhD program? As you look at the "Data Science Venn Diagram" or the "Becoming a Data Scientist – Curriculum via Metromap" do you find yourself wondering if you have what it takes to make it? The following steps will help ease your concerns...
  • Learning World Graphs to Accelerate Hierarchical Reinforcement Learning
    An autonomous agent often counters various tasks within a single complex environment. Our two-stage framework proposes to first build a simple directed weighted graph abstraction over the world in an unsupervised task-agnostic manner and then to accelerate the hierarchical reinforcement learning of a diversity of downstream tasks...
  • Visual Wake Words Dataset
    I've created a python library to work with the Visual Wake Words Dataset, comparable to how pycocotools works with the COCO dataset. Also included is a PyTorch Dataset class which can used like any VisionDataset...


  • The Lady Tasting Tea:
    How Statistics Revolutionized Science in the Twentieth Century

    An insightful, revealing history of how mathematics transformed our world...
    "I have taken courses in statistics, taught it many times and solved several statistical problems that have appeared in journals. But until I read this book, I never really thought about it in so deep and philosophical a manner..."

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


P.S., Enjoy the newsletter? Please forward it to your friends and colleagues - we'd love to have them onboard :) All the best, Hannah & Sebastian

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