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Data Science Weekly Newsletter
July 19, 2018

Editor's Picks

  • AI is getting closer to replacing animal testing
    An artificial intelligence system published in the research journal Toxicological Sciences shows that it might be possible to automate some tests using the knowledge about chemical interactions we already have. The AI was trained to predict how toxic tens of thousands of unknown chemicals could be, based on previous animal tests, and the algorithm’s results were shown to be as accurate as live animal tests...The algorithm can predict results from nine different tests, from skin corrosion to eye irritation, which authors say comprised 57% of all animal testing done in the EU in 2011...
  • What do machine learning practitioners actually do?
    In thinking about how we can automate some of the work of machine learning, as well as how to make it more accessible to people with a wider variety of backgrounds, it’s first necessary to ask, what is it that machine learning practitioners do? Any solution to the shortage of machine learning expertise requires answering this question: whether it’s so we know what skills to teach, what tools to build, or what processes to automate...
  • How to Find Underrated People on Twitter
    This great advice from Tyler Cowen (economist and blogger at Marginal Revolution) got me thinking: What are some strategies for finding talented but underrated people?...

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Data Science Articles & Videos

  • Autopsy Of A Deep Learning Paper
    I read a lot of deep learning papers, typically a few/week. I've read probably several thousands of papers. My general problem with papers in machine learning or deep learning is that often they sit in some strange no man's land between science and engineering, I call it "academic engineering". Let me describe what I mean...
  • Carlsberg Research Laboratory behind beer research project based on AI
    Today a multi-million-dollar investment is announced in a research study with the purpose of measuring and sensing flavours and aromas in beer. The research study called ‘The Beer Fingerprinting Project’ was founded on the idea of Jochen Förster from Carlsberg Research Laboratory...
  • AI Innovators:
    How One Woman Followed Her Passion and Brought Diversity to AI

    Meet Timnit Gebru. Born and raised in Ethiopia, Gebru immigrated to the US at 16 to earn her PhD from Stanford Artificial Intelligence Laboratory and just finished her year as a post-doctoral researcher at Microsoft Research in New York. While she was still a PhD student, she co-founded Black in AI, an organization fostering collaboration and discussing initiatives to increase the representation of Black people in the field...
  • Takeaways from Netflix’s Personalization Workshop 2018
    For the third time Netflix organized its Personalization, Recommendation and Search Workshop...There was one subject that all speakers agreed on: classic matrix factorization (collaborative filtering) reached its expiration date. This blog captures my takeaways on their different approaches for its successor. This includes challenges of multi-armed bandits, an implicit feedback approach, top-N ranking techniques, tyranny of the majority and algorithmic bias...
  • On “solving” Montezuma’s Revenge -
    Looking beyond the hype of recent Deep RL successes

    In this post, I want to discuss what these methods do in order to solve the first level of Montezuma’s Revenge, and why in the context of the game, and long-term goals for Deep RL, this approach isn’t as interesting or meaningful as it might seem. Finally, I will briefly discuss what I would see as truly impressive results on the notorious game, one which would point the way forward for the field...
  • Training and serving a realtime mobile object detector in 30 minutes with Cloud TPUs
    What if you could train and serve your object detection models even faster? We’ve heard your feedback, and today we’re excited to announce support for training an object detection model on Cloud TPUs, model quantization, and the addition of new models including RetinaNet and a MobileNet adaptation of RetinaNet. You can check out the announcement post on the AI blog. In this post, we’ll walk you through training a quantized pet breed detector on Cloud TPUs using transfer learning...
  • Seedbank — discover machine learning examples
    Google's Seedbank is a collection of Interactive Machine Learning Examples. These are interactive machine learning examples which you can run from your browser, no set-up required. Each example is a little seed to inspire you that you can edit, extend, and grow into your own projects and ideas, from data analysis problems to art projects...
  • Reinforcement learning’s foundational flaw
    Here’s the basic question: how reasonable is it to design AI models based on pure RL if pure RL makes so little intuitive sense? If it’s so absurd to conceive of a human learning a new board game through pure RL, shouldn’t we wonder if it's a flawed framework for how AI agents should learn? Does it really make sense to start learning a new skill based only on its reward signal, with neither prior experience nor higher-level instruction?...


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Training & Resources

  • AutoGraph converts Python into TensorFlow graphs
    Writing TensorFlow code without using eager execution requires you to do a little metaprogramming — -you write a program that creates a graph, and then that graph is executed later. This can be confusing, especially for new’d like to tell you about a new TensorFlow feature called “AutoGraph”. AutoGraph converts Python code, including control flow, print() and other Python-native features, into pure TensorFlow graph code...
  • Simple API for UCI Machine Learning Dataset Repository
    (search, download, analyze)

    UCI machine learning dataset repository is something of a legend in the field of machine learning pedagogy. It is a 'go-to-shop' for beginners and advanced learners alike. This codebase is an attempt to present a simple and intuitive API for UCI ML portal, where users can easily look up a dataset description, search for a particular dataset they are interested, and even download datasets categorized by size or machine learning task...


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