Receive the Data Science Weekly Newsletter every Thursday

Easy to unsubscribe at any time. Your e-mail address is safe.

Data Science Weekly Newsletter
Issue
262
November 29, 2018

Editor's Picks

  • GANpaint: Paint with GAN units
    GANPaint draws with object-level control using a deep network. Each brush activates a set of neurons in a GAN that has learned to draw scenes...
  • How Cheap Labor Drives China’s A.I. Ambitions
    Some of the most critical work in advancing China’s technology goals takes place in a former cement factory in the middle of the country’s heartland, far from the aspiring Silicon Valleys of Beijing and Shenzhen. An idled concrete mixer still stands in the middle of the courtyard. Boxes of melamine dinnerware are stacked in a warehouse next door...



A Message From This Week's Sponsor


 
Find A Data Science Job Through Vettery

Vettery specializes in tech roles and is completely free for job seekers. Interested? Submit your profile, and if accepted onto the platform, you can receive interview requests directly from top companies growing their data science teams.
Get started.


Data Science Articles & Videos

  • Uber AI ‘reliably’ completes all stages in Montezuma’s Revenge
    Montezuma’s Revenge is a notoriously difficult video game for humans, much less artificial intelligence (AI), to beat — the first level alone consists of 24 rooms filled with traps, ropes, ladders, enemies, and concealed keys. But recently, AI systems from OpenAI, Google’s DeepMind, and others have managed to make impressive gains. And this week, new research from Uber raises the bar higher still with GoExplore...
  • Quick Opinions on Go-Explore
    This was originally going to be a Tweetstorm, but then I decided it would be easier to write as a blog post. Today, Uber AI Labs announced that they had solved Montezuma’s Revenge with a new algorithm called Go-Explore. These are eye-popping headlines, but there’s controversy around the results, and I have opinions here...
  • Hierarchical visuomotor control of humanoids
    Our agent combines visual perception and motor control to solve tasks in simulated physical environments: We aim to build complex humanoid agents that integrate perception, motor control, and memory. In this work, we partly factor this problem into low-level motor control from proprioception and high-level coordination of the low-level skills informed by vision...
  • Structured Approach to Unsupervised Depth Learning from Monocular Videos
    We propose a novel approach which is able to model moving objects and produces high quality depth estimation results. Our approach is able to recover the correct depth for moving objects compared to previous methods for unsupervised learning from monocular videos. In our paper, we also propose a seamless online refinement technique that can further improve quality and be applied for transfer across datasets. Furthermore, to encourage even more advanced approaches of onboard robotics learning, we have open sourced the code in TensorFlow...
  • Ganbreeder
    Ganbreeder is a collaborative art tool for discovering images. Images are 'bred' by having children, mixing with other images and being shared via their URL. This is an experiment in using breeding + sharing as methods of exploring high complexity spaces. GAN's are simply the engine enabling this...
  • Amazon Comprehend Medical –
    Natural Language Processing for Healthcare Customers

    As the son of a Gastroenterologist and a Dermatologist, I grew up listening to arcane conversations involving a never-ending stream of complex medical terms: human anatomy, surgical procedures, medication names… and their abbreviations. A fascinating experience for a curious child wondering whether his parents were wizards of some sort and what all this gibberish meant. For this reason, I am very happy to announce Amazon Comprehend Medical, an extension of Amazon Comprehend for healthcare customers...
  • Towards Reinforcement Learning Inspired By Humans Without Human Demos
    We present the Strategic Object-Oriented RL (SOORL) algorithm which is the first algorithm to our knowledge that can achieve positive rewards on the notoriously hard Atari game Pitfall! without access to human demonstrations, and can do so within 50 episodes. SOORL uses stronger prior knowledge (access to objects in the environment and a class of potential dynamics model) than standard deep RL algorithms, but much weaker information than methods that require access to trajectories of decent human play...



Jobs

  • Data Scientist - Wegmans - Rochester, NY

    There’s never been a better time to be on the Consumer Insights Team at Wegmans! Wegmans is on a journey to transform its digital strategy and we are quickly growing our digital and e-commerce businesses. You’ll be part of a new team of Data Scientists that support our Marketing and Merchandising teams with providing important customers insights that help our business leaders make quick decisions. If you are a creative and passionate problem-solver who can think big, work quickly and are motivated to develop new ways to optimize our business, this could be the job for you!...


Training & Resources


Books


  • Seven Databases in Seven Weeks:
    A Guide to Modern Databases and the NoSQL Movement

    "A book that tries to cover multiple database is a risky endeavor, a book that also provides hands on on each is even riskier but if implemented well leads to a great package. I loved the specific exercises the authors covered. A must read for all big data architects who don’t shy away from coding..."...
    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page


Easy to unsubscribe at any time. Your e-mail address is safe.