Data Science Weekly Newsletter - Issue 271

Issue #271

Jan 31 2019

Editor Picks
 
  • Why are Machine Learning Projects so Hard to Manage?
    I’ve watched lots of companies attempt to deploy machine learning — some succeed wildly and some fail spectacularly. One constant is that machine learning teams have a hard time setting goals and setting expectations. Why is this?...
  • Predicting a Startup Valuation with Data Science
    The following is a condensed and slightly modified version of a Radicle working paper on the startup economy in which we explore post-money valuations by venture capital stage classifications. We find that valuations have interesting distributional properties and then go on to describe a statistical model for estimating an undisclosed valuation with considerable ease...
  • Fuelled by Data: How to Pace the London Marathon
    As a self-confessed running addict, this was an opportunity to dive into some juicy running data. And which race to analyse? Only the best race in the world would do: the London Marathon...
 
 

A Message from this week's Sponsor:

 

 
The sins of recruitment

These days you’re likely to encounter bad dating behaviours in the hunt for your dream job as you are for your dream date. In fact a shocking 90% of job hunters have claimed to experience one of the notorious ‘recruiting sins’.
   

 

Data Science Articles & Videos

 
  • Towards reconstructing intelligible speech from the human auditory cortex
    Thanks to fMRI scanning, we’ve known for decades that when people speak, or hear others, it activates specific parts of their brain. However, it’s proved hugely challenging to translate thoughts into words. A team from Columbia University has developed a system that combines deep learning with a speech synthesizer to do just that...
  • Obstacle Tower Environment
    The Obstacle Tower is a procedurally generated environment consisting of multiple floors to be solved by a learning agent. It is designed to test learning agents abilities in computer vision, locomotion skills, high-level planning, and generalization. It combines platforming-style gameplay with puzzles and planning problems, and critically, increases in difficult as the agent progresses...
 
 

Jobs

 
  • Quantitative Behavioral Scientist - BetterUp - San Francisco, remote ok

    BetterUp Labs is currently seeking an innovative, early-career quantitative behavioral scientist who is passionate about advancing our understanding of the inner life and whole person performance of professionals around the globe. You will help design and implement original research to learn more about what makes us tick when we’re at work. You’ll need to draw on your budding experience as an experimental social scientist, inferential statistician, computational scientist, and lover of all things Data to uncover the truly groundbreaking answers to these questions...

        Want to post a job here? Email us for details >> team@datascienceweekly.org
 

 

Training & Resources

 
  • How to Subclass The nn.Module Class in PyTorch
    Learn how to construct a Custom PyTorch Model by creating your own custom PyTorch module by subclassing the PyTorch nn.Module class, via a screencast video and full tutorial transcript...
 
 

Books

 

  • The Book of R: A First Course in Programming and Statistics

    "The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis"...


    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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