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Data Science Weekly Newsletter
February 22, 2018

Editor's Picks

  • Pommerman
    Announcing a new Machine Learning Challenge for AI: Pommerman! Based on the classic game Bomberman. Train your team of AI agents. Compete against everyone else's...

A Message From This Week's Sponsor

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  • Jim Guszcza, Chief Data Scientist at Deloitte Consulting
  • Max Shron, Head of Data Science at Warby Parker
  • Chad Wilsey, Director of Conservation Science at Audubon
  • And many more!
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Data Science Articles & Videos

  • Deep Learning, Structure and Innate Priors
    Earlier this month, I had the exciting opportunity to moderate a discussion between Professors Yann LeCun and Christopher Manning, titled “What innate priors should we build into the architecture of deep learning systems?” This discussion topic – about the structural design decisions we build into our neural architectures, and how those correspond to certain assumptions and inductive biases – is an important one in AI right now...
  • What is a Senior Data Visualization Engineer?
    I was asked recently on twitter a question that I’ve been asked in one form or another several times since I became a Senior Data Visualization Engineer at Netflix: can you explain to me what a Senior Data Visualization Engineer exactly does?...
  • Hey Maggie
    A TensorFlow-based Android app for translating baby noises into English! It sounds like science-fiction, but it's written by a child development researcher who taught himself ML...
  • New benchmarks for approximate nearest neighbors
    One of my super nerdy interests include approximate algorithms for nearest neighbors in high-dimensional spaces. The problem is simple. You have say 1M points in some high-dimensional space. Now given a query point, can you find the nearest points out of the 1M set? Doing this fast turns out to be tricky...


  • VP, Data Science - Diply - Toronto
    Diply VP of Data Science, Machine Learning and AI, will have the opportunity to build a superstar data science team from the ground up, both setting the strategy and ensuring tactical execution.
    You will partner with business stakeholders to identify and prioritize top Data Science and AI opportunities, create business/technical requirements, transform over 50B monthly records of data into scientific models and AI-driven solutions, lead ML strategy and roadmap planning, and build out the data science and AI teams. The ideal leader will combine expert Data Science/AI/ML knowledge with hands on experience building algorithms/models/programming and outstanding management skills in managing teams and delivering complex/critical projects. Media industry experience is an asset...

Training & Resources

  • Learning Explanatory Rules from Noisy Data
    Artificial Neural Networks are powerful function approximators capable of modelling solutions to a wide variety of problems, both supervised and unsupervised. As their size and expressivity increases, so too does the variance of the model, yielding a nearly ubiquitous overfitting problem...


  • Bit by Bit: Social Research in the Digital Age
    "The book goes well beyond "big data" to unpack the possibilities of doing social science research at a massive scale, and relatively inexpensively. This book should be read by social scientists who want to expand their research horizons, data scientists who want to understand how to incorporate the insights of social science, and anyone in a line of work in which they have potential data that can give them insights into how people behave..."...
    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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