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Data Science Weekly Newsletter
February 14, 2019

Editor's Picks

A Message From This Week's Sponsor

Themes and Conferences per Pacoid, Episode 6

In Paco Nathan's latest column, he explores the role of curiosity in data science work as well as Rev 2
, an upcoming summit for data science leaders. This episode unpacks curiosity as a core attribute of effective data science, looks at how that informs process for data science (in contrast to Agile, etc.), and digs into details about where science meets rhetoric in data science. Overall, these topics are among the themes you can expect at the next Rev
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Data Science Articles & Videos

  • Pricing algorithms can learn to collude with each other to raise prices
    Pricing algorithms have become ubiquitous in online retail as automated systems have grown increasingly affordable and easy to implement. But while companies like airlines and hotels have long used machines to set their prices, pricing systems have evolved. They have moved from rule-based programs to reinforcement-learning ones, where the logic of deciding a product’s price is no longer within a human’s control...
  • Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
    The posteriors over neural network weights are high dimensional and multimodal. Each mode typically characterizes a meaningfully different representation of the data. We develop Cyclical Stochastic Gradient MCMC (SG-MCMC) to automatically explore such distributions. In particular, we propose a cyclical stepsize schedule, where larger steps discover new modes, and smaller steps characterize each mode. We prove that our proposed learning rate schedule provides faster convergence to samples from a stationary distribution than SG-MCMC with standard decaying schedules...
  • What Trump's Executive Order on AI is missing
    President Trump signed an executive order on February 11 meant to shore up our competitive position in the international race for AI supremacy, but it is short on concrete steps. As the CEO of an artificial intelligence research institute, I am calling on him to include a special visa program for AI students and experts to help us win this race for the sake of both economic vitality and national security...


A$1 million on a journey to discovery with data

The Explorer Challenge starts 28 February. Can you find Australia’s next big mineral deposit? Apply your data science skills to help unearth the next generation of exploration in Australia, using real industry data.
Find out more and register:


  • Data Scientist - TRANZACT - Fort Lee, 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 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...
        Want to post a job here? Email us for details >>

Training & Resources

  • Calculate TensorFlow Median Value
    Learn how to calculate TensorFlow Median Value using the percentile distribution and the interpolation methods, via a screencast video and full tutorial transcript...
  • Tensor Variable Elimination for Plated Factor Graphs
    To exploit efficient tensor algebra in graphs with plates of variables, we generalize undirected factor graphs to plated factor graphs and variable elimination to a tensor variable elimination algorithm that operates directly on plated factor graphs...
  • JAX: Autograd and XLA
    Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more ... basically NumPy with gradients. And it can compile to XLA, for strong GPU/TPU acceleration. It's an ideal fit for researchers who want maximum flexibility when implementing new ideas from scratch...


  • The Book of R: A First Course in Programming and Statistics
    "The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis"...

    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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