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Data Science Weekly Newsletter
November 21, 2019

Editor's Picks

  • Increasing transparency with Google Cloud Explainable AI
    We are excited to announce our latest step in improving the interpretability of AI with Google Cloud AI Explanations. Explanations quantifies each data factor’s contribution to the output of a machine learning model. These summaries help enterprises understand why the model made the decisions it did. You can use this information to further improve your models or share useful insights with the model’s consumers....
  • Deep Learning with PyTorch
    To help developers get started with PyTorch, we’re making the 'Deep Learning with PyTorch' book, written by Luca Antiga and Eli Stevens, available for free to the community...
  • Safety Gym
    We’re releasing Safety Gym, a suite of environments and tools for measuring progress towards reinforcement learning agents that respect safety constraints while training...

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Data Science Articles & Videos

  • It's Sony AI vs. Facebook, Google
    Sony Corp. has launched Sony AI, a new organization to pursue advanced R&D in artificial intelligence. With this move, the Japanese consumer electronics giant intends to go head-to-head with Google and Facebook, competing for AI talent and projects, and targeting a much bigger role in an ever-accelerating global AI race...
  • How to recognize AI snake oil
    Much of what’s being sold as “AI” today is snake oil — it does not and cannot work. Why is this happening? How can we recognize flawed AI claims and push back?...
  • Teachable Machine
    Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more...
  • RecSim: A Configurable Simulation Platform for Recommender Systems
    We have developed RecSim(available here), a configurable platform for authoring simulation environments to facilitate the study of RL algorithms in recommender systems (and CIRs in particular). RecSim allows both researchers and practitioners to test the limits of existing RL methods in synthetic recommender settings...
  • Building A Data Science Portfolio Project Bottom Up
    You are going to build a data science portfolio in order to showcase your skills. You will use it in order to attract potential employers, as well as something to speak about during the actual interview. You have a few ideas of projects. The question now becomes, what do you do next... This article, will cover the basics of the bottom up approach - starting with the data...


Create D3 Data Visualizations As Fast As You Can Sketch

You need to create a D3.js data visualization to communicate your insights. But... #d3BrokeAndMadeArt! This time, your data join appears to have broken and the JavaScript console shows an error you don't recognize. Last time, you got stuck trying to figure out how to make axes that didn't look like 3rd graded made them. It makes you want to strangle D3 with your bare hands. Just how steep does the D3 learning curve need to be?!
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  • Data Scientist - Driven Brands - Charlotte, NC

    The Data Scientist for Driven Brands focus will be responsible for providing reliable marketing, media and promotional performance analysis and reporting to Senior Executives and Business Unit Management to be used to make decisions impacting the performance of the business...
        Want to post a job here? Email us for details >>

Training & Resources

  • TensorFlow Lite Transformers w/ Android demo
    Convert Transformers models imported from the 🤗 Transformers library and use them on Android. You can also check out our swift-coreml-transformers repo if you're looking for Transformers on iOS...
  • Faster Neural Networks Straight from JPEG
    In this article, we describe an approach presented at NeurIPS 2018 for making CNNs smaller, faster, and more accurate all at the same time by hacking libjpeg and leveraging the internal image representations already used by JPEG, the popular image format...


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