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Data Science Weekly Newsletter
December 19, 2019

Editor's Picks

  • Key trends from NeurIPS 2019
    With 51 workshops, 1428 accepted papers, and 13k attendees, saying that NeurIPS is overwhelming is an understatement. I did my best to summarize the key trends I got from the conference...
  • Why video games and board games aren’t a good measure of AI intelligence
    Beating humans at chess and Go is impressive, yes, but what does it matter if the smartest computer can be out-strategized in general problem-solving by a toddler or a rat? This is a criticism put forward by AI researcher François Chollet, a software engineer at Google and a well-known figure in the machine learning community. Chollet is the creator of Keras, a widely used program for developing neural networks, the backbone of contemporary AI. In this interview, we learn more...

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Data Science Articles & Videos

  • NeurIPS 2019 featured robot curling players and coffee makers
    One particularly active category of research this year was robotics, which saw workshop and paper contributions from Intel, the University of California at Berkeley, and other leaders. Perhaps the most intriguing of these were novel approaches to training a team of machines to jointly solve a problem, and a multi-stage learning technique that uses pixel-level translation of human videos to train robots to complete tasks...
  • SynSin: End-to-end View Synthesis from a Single Image
    Single image view synthesis allows for the generation of new views of a scene given a single input image. This is challenging, as it requires comprehensively understanding the 3D scene from a single image. As a result, current methods typically use multiple images, train on ground-truth depth, or are limited to synthetic data. We propose a novel end-to-end model for this task; it is trained on real images without any ground-truth 3D information...
  • Famous Fluid Equations Spring a Leak
    Mathematicians have suspected for years that under specific circumstances, the Euler equations fail. But they’ve been unable to identify an exact scenario in which this failure occurs. Until now....


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    JetBlue is seeking a Data Science Manager to lead a team of data scientists who will design experiments and develop machine learning models to address the company’s most complex data problems. We are looking for an experienced data scientist with broad knowledge of machine learning and statistical techniques. This individual will establish best practices for data science workflows and knows how to create an environment that enables data scientists to perform at their best. Beyond a great culture, the benefits (free flights!) are hard to beat...
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Training & Resources

  • An Introduction to Neural Information Retrieval
    This tutorial introduces basic concepts and intuitions behind neural IR models, and places them in the context of classical non-neural approaches to IR. We begin by introducing fundamental concepts of retrieval and different neural and non-neural approaches to unsupervised learning of vector representations of text. We then review IR methods that employ these pre-trained neural vector representations without learning the IR task end-to-end...
  • Generative Teaching Networks
    This video explores an exciting new Meta Learning paper in which the classifier learns its own training data! This video will explore the application of this to Neural Architecture Search, weight normalization, and the use of curriculum learning!...
  • Common Voice: A Massively-Multilingual Speech Corpus
    The Common Voice corpus is a massively-multilingual collection of transcribed speech intended for speech technology research and development. The most recent release includes 29 languages, and as of November 2019 there are a total of 38 languages collecting data. Over 50,000 individuals have participated so far, resulting in 2,500 hours of collected audio...


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  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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