Data Science Weekly Newsletter - Issue 64

Issue #64

Feb 12 2015

Editor Picks
   
 

A Message from this week's Sponsor

 

  • Want to be a Data Scientist, but don't know where to start?
    Learn essential Data Science skills in SlideRule's Intro to Data Science Workshop. In this online bootcamp, you'll learn R, data wrangling, analytics and visualization by working on real projects, with 1-on-1 mentorship from expert Data Scientists from LinkedIn, Glassdoor, Trulia and Stripe.

    Spots are limited; registration ends in 48 hours!
 
 

Data Science Articles & Videos

 
  • Machine Learning For Journalism at The New York Times
    Daeil Kim is a Data Scientist at the New York Times, a role which has crystallised his research work into the niche between Machine Learning and Journalism. Kim spoke at the New York Data Science Meetup last week about how to make journalists work easier by using Machine Learning, a Bayesian perspective on big data and a discreet section on non journalistic related Machine Learning at the NYT...
  • Automating Tinder with Eigenfaces
    While my friends were getting sucked into "swiping" all day on their phones with Tinder, I eventually got fed up and designed a piece of software that automates everything on Tinder...
  • Bayesian Statistics as a way to integrate Intuition and Data
    John D. Cook spoke at KeenCon to talk to us about Bayesian Statistics as a Way to Integrate Intuition and Data. This is a mathematical framework for expressing what you believe, including your uncertainty, and rationally updating your beliefs as data become available...
  • 10 Machine Learning Lessons Harnessed By Netflix
    Xavier Amatriain guided Netflix through a considerable programme of research to make sure the most appropriate and efficient techniques were being used in order to personalise the Netflix product for users. In this Slideshare, he talks about some of the lessons they learned from building ML systems and concludes how choosing the right metric and understanding dependencies between data and models are vital...
  • You Can Be A Data Analyst Without Doing Heavy Math
    When you read online descriptions of data analyst jobs do you feel like you’re not qualified? Do you feel like a cycle repair technician because you aren’t working with terabyte databases, running PhD-level math equations, and implementing your own machine learning algorithms?...
  • Text Understanding from Scratch
    This article demontrates that we can apply deep learning to text understanding from character-level inputs all the way up to abstract text concepts, using temporal convolutional networks (ConvNets)...
  • Most Popular Coding Languages of 2015
    Every year, we publish data on the "Most Popular Coding Languages" based on hundreds of thousands of data points we've collected by processing over 600,000+ coding tests and challenges by over 2,000+ employers...
 
 

Jobs

 
  • Lead Data Scientist - Athos - SF Bay

    At Athos we’re developing a new class of products that brings unparalleled insight to fitness and athletics. Athos is performance apparel measuring muscle intensity, heart rate and breathing rate served up through a beautiful app experience.

    Data and its analysis is at the heart of what we do, from distilling complex science down to digestible insight, unlocking new product features and validating/benchmarking the performance of the product. We are looking for the right person to lead our data science and analytics efforts...
 
 

Training & Resources

 
  • Getting Started with Spark (in Python)
    In this post we will first discuss how to set up Spark to start easily performing analytics, either simply on your local machine or in a cluster on EC2. We then will explore Spark at an introductory level, moving towards an understanding of what Spark is and how it works...
  • Neural network with numpy
    Neural networks are a pretty badass machine learning algorithm for classification. For me, they seemed pretty intimidating to try to learn but when I finally buckled down and got into them it wasn't so bad...
 
 

Books

 

  • The Lady Tasting Tea:
    How Statistics Revolutionized Science in the Twentieth Century

    An insightful, revealing history of how mathematics transformed our world...

    "I have taken courses in statistics, taught it many times and solved several statistical problems that have appeared in journals. But until I read this book, I never really thought about it in so deep and philosophical a manner..."

    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
 
 
P.S. Enjoyed the newsletter? Please forward it along to friends and colleagues - we'd love to have them onboard! - All the best, Hannah & Sebastian
 
Sign up to receive the Data Science Weekly Newsletter every Thursday

Easy to unsubscribe. No spam — we keep your email safe and do not share it.