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Data Science Weekly Newsletter
February 21, 2019

Editor's Picks

  • How We Created a Visual Search Engine for
    This post explains the visual search project we did for Hayneedle, a home furnishings and decor retailer part of our larger Walmart family of brands. My team was tasked with creating a search experience for customers that would allow them to search for products purely through images instead of words...
  • How 20th Century Fox uses ML to predict a movie audience
    Historically, movie studios have relied heavily on experience when deciding to invest in a particular script—but this can lead to huge risks, particularly when investing in new, original stories. The iterative and complex process of matching stories and audiences is something that Julie Rieger, President, Chief Data Strategist and Head of Media, and Miguel Campo-Rembado, SVP of Data Science, together with their team of data scientists at 20th Century Fox, decided to clarify with data...

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Data Science Articles & Videos

  • Keeping up with AI in 2019
    The past year has been rich in events, discoveries and developments in AI. It is hard to sort through the noise to see if the signal is there and, if it is, what is the signal saying. This post attempts to get you exactly that: I’ll try to extract some of the patterns in the AI landscape over the past year. And, if we are lucky, we’ll see how some of the trends extend into the near future...
  • Better Language Models and Their Implications
    We’ve trained a large-scale unsupervised language model which generates coherent paragraphs of text, achieves state-of-the-art performance on many language modeling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarization — all without task-specific training...
  • Data Science Foundations: Know your data. Really, really, know it
    Know your data, where it comes from, what’s in it, what it means. It all starts from there. If there is one piece of advice that I consistently give to every data person that’s starting out, whether they are going to be an analyst, scientist, or visualizer, this is it. This is the hill I spend the majority of my time on even now, to the point of obsession. It is a deeeeeeep but eminently important rabbit hole...
  • Self driving remote-control car with Apache MXNet
    Autonomous driving is one of the most high-profile applications of deep learning. Recently AWS announced DeepRacer, a fully autonomous 1/18th scale race car driven by reinforcement learning. In this post I’ll show new-comers to machine learning how to assemble their very own self-driving remote control car and use Apache MXNet to teach it to race on a track...
  • Emergent Coordinated Multi-Agent Behaviors through Competition
    We study the emergence of cooperative behaviors in reinforcement learning agents using a challenging competitive multi-agent soccer environment with continuous simulated physics. We demonstrate that decentralized, population-based training with co-play can lead to a progression in agents' behaviors: from random, to simple ball chasing, and finally showing evidence of cooperation...
  • Data science is different now
    For the past couple years, I've been telling people who ask me for advice not to go into data science. Here's why: The data science job market is way oversaturated. Here's what they should do instead...


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.
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  • 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...
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Training & Resources


  • 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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