Data Science Weekly Newsletter - Issue 261

Issue #261

Nov 22 2018



Many of you reached out last week to congratulate us on the 5th year anniversary of the DSW newsletter - it meant a lot and was great to hear from you, so thank you all!

One of the common asks was to add a donation button this week so you could thank us for the work so far and encourage us to keep going ... so here we go!



Looking forward to many more newsletters!
Editor Picks
 
  • Mapping The AI toolchain
    Access to AI will be democratized. During this transition, we believe AI – particularly deep learning – will begin to resemble a general-purpose computing platform. But a new set of tools will be necessary to make that vision a reality. To advance the conversation, we are publishing an alpha landscape of the emerging AI Toolchain...
  • Arbitrary Image Stylization in the Browser
    This is an implementation of an arbitrary image stylization algorithm running purely in the browser using TensorFlow.js. As with all neural style transfer algorithms, a neural network attempts to "draw" one picture, the Content (usually a photograph), in the style of another, the Style (usually a painting)...
 
 

A Message from this week's Sponsor:

 

 
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Data Science Articles & Videos

 
  • Discovery of independently controllable features through autonomous goal setting
    Despite recent breakthroughs in artificial intelligence, machine learning agents remain limited to tasks predefined by human engineers. The autonomous and simultaneous discovery and learning of many-tasks in an open world remains very challenging for reinforcement learning algorithms. In this blog post we explore recent advances in developmental learning to tackle the problems of autonomous exploration and learning...
  • Rethinking ImageNet Pre-training
    We report competitive results on object detection and instance segmentation on the COCO dataset using standard models trained from random initialization....
  • A Convergence Theory for Deep Learning via Over-Parameterization
    In this work, we prove why simple algorithms such as stochastic gradient descent (SGD) can find global minima on the training objective of DNNs. We only make two assumptions: the inputs do not degenerate and the network is over-parameterized ... solving one of the most important unsolved problems in DNN ...
 
 
 

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

 
  • Flatten A PyTorch Tensor
    Learn how to flatten a PyTorch Tensor by using the PyTorch view operation, via a screencast video and full tutorial transcript...
  • PySyft Step-By-Step Tutorial
    In this step-by-step tutorial series, you'll learn about all the ways PySyft can be used to bring Privacy and Decentralization to the Deep Learning ecosystem. This tutorial series is continually updated with new features as they are implemented, and is designed for complete beginners...
 

 

Books

 

  • Data Smart: Using Data Science to Transform Information into Insight

    "The best single book on Data Science today. I handle the data analysis and BI for the delivery side of a huge internet-based retail company, and have been a fan of Foreman's since his "Analytics Made Skeezy" blog days. His explanations are clear, his examples are to the point, and throughout it all, he is results-oriented."...


    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
     

     
    P.S., Want to reach our audience / fellow readers? Consider sponsoring - grab a spot now; first come first served! All the best, Hannah & Sebastian
 
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