Data Science Weekly Newsletter - Issue 135

Issue #136

June 30 2016

Editor Picks
   
 

A Message from this week's Sponsor:

 

 
 

Data Science Articles & Videos

 
  • How well do facial recognition algorithms cope with a million strangers?
    In the last few years, several groups have announced that their facial recognition systems have achieved near-perfect accuracy rates, performing better than humans at picking the same face out of the crowd. But those tests were performed on a dataset with only 13,000 images — fewer people than attend an average professional U.S. soccer game. What happens to their performance as those crowds grow to the size of a major U.S. city?...
  • Why We Should Expect Algorithms to Be Biased
    Technologies driven by algorithms and artificial intelligence are increasingly present in our lives, and we are now regularly bumping up against a thorny question: can these programs be neutral actors? Or will they always reflect some degree of human bias?...
  • The making and comparison of draft curves
    Despite the growing popularity of drafts in each sport, I was disappointed to find that there are apparently (a) No open-source guideline for how to make a draft curve and/or value chart; (b) No attempt at comparing each of the sports’ draft curves simultaneously. Those will be my goals here...
  • Anticipating Visual Representations from Unlabeled Video
    Anticipating actions and objects before they start or appear is a difficult problem in computer vision with several real-world applications. We present a framework that capitalizes on temporal structure in unlabeled video to learn to anticipate human actions and objects...
  • Detecting Money Laundering
    Applying machine learning to AML has been challenging due to the limited availability of labeled datasets. However there are a number of unsupervised techniques that may be worth considering...
  • Human Or Machine: Can You Tell Who Wrote These Poems?
    Can a computer write a sonnet that's indistinguishable from what a human can produce? Computer scientists at Dartmouth College tried to answer that question with a competition that NPR's Joe Palca reported on as part of his series, Joe's Big Idea...
 
 

Jobs

 
  • Data Scientist - Uber - NYC

    For Uber to be a world-class transportation option for everyone, it must be one thing first - Reliable. The Monitoring Platform is about bringing world-class thinking around anomaly detection, trace analysis, root cause detection, and machine learning on a large scale to help build technology to guarantee that the Uber experience is always excellent...
 
 

Training & Resources

 
  • Hello, TensorFlow!
    Building and training your first TensorFlow graph from the ground up...
  • open-source-society/data-science
    This is a solid path for those of you who want to complete a Data Science course on your own time, for free, with courses from the best universities in the World. In our curriculum, we give preference to MOOC (Massive Open Online Course) style courses because these courses were created with our style of learning in mind...
 
 

Books

 

  • Data Scientists At Work

    A collection of interviews with sixteen of the world's most influential and innovative data scientists...


    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
 
 
P.S. Interested in reaching fellow readers of this newsletter? Consider sponsoring! Email us for details :) - All the best, Hannah & Sebastian
 
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