Data Science Weekly Newsletter - Issue 95

Issue #95

September 17 2015

Editor Picks
 
  • Intelligent machines: Making AI work in the real world
    As part of the BBC's Intelligent Machines season, Google's Eric Schmidt has penned an exclusive article on how he sees artificial intelligence developing, why it is experiencing such a renaissance and where it will go next...
 
 

A Message from this week's Sponsor:

 

 
 

Data Science Articles & Videos

 
  • Sharks, Landsharks, Geoplotting, and KDTrees!
    So now with the end of summer officially here (at least in the northern hemisphere), we thought it would be interesting to dig into some shark attack data. In this post, we'll look through the Global Shark Attack File, checkout some of the characteristics of shark attacks and then dive in to some geo-plotting with Matplotlib Basemap...
  • Letting Users Choose Recommender Algorithms: An Experimental Study
    As one way of taking advantage of the relative merits of different algorithms, we gave users the ability to change the algorithm providing their movie recommendations and studied how they make use of this power... We examine log data from user interactions with this new feature to understand whether and how users switch among recommender algorithms, and select a final algorithm to use...
  • Machine Learning Trick of the Day: Hutchinson's Trick
    Hutchinson's estimator is a simple way to obtain a stochastic estimate of the trace of a matrix. This is a simple trick that uses randomisation to transform the algebraic problem of computing the trace into the statistical problem of computing an expectation of a quadratic function...
  • Forget Dark Energy: MIT Physicists Have Finally Cracked Overhand Knots
    In a study recently accepted for publication in the Physical Review Letters, engineers at MIT and Pierre et Marie Curie University in Paris offer a new fundamental theory of knots based on relationships between topology, the mathematics of spatial relationships, and the basic mechanics of friction and pliability...
 
 

Jobs

 
  • Data Scientist - Trunk Club - Chicago

    At Trunk Club, we develop services that help our employees make data-driven decisions, from stylists to merchandising. Every team at Trunk Club relies on the data we collect about our customers and how we interact with them to make meaningful decisions. Our tool chain strives to make it easy and painless to turn an algorithm into an API or run A/B tests using multivariate models. Our work drives Trunk Club - we enable the entire company to iterate faster and help accelerate business growth. You will have visibility into every team and be connected directly to executives without bureaucracy...
 
 

Training & Resources

 
  • Cheatsheet – Python & R codes for common Machine Learning Algorithms
    Here’s a collection of 10 most commonly used machine learning algorithms with their codes in Python and R. Considering the rising usage of machine learning in building models, this cheat sheet is good to act as a code guide to help you bring these machine learning algorithms to use...
 
 

Books

 

  • The Signal and the Noise: Why So Many Predictions Fail — but Some Don't

    Very well reviewed...

    "This is the best general-readership book on applied statistics that I've read. Short review: if you're interested in science, economics, or prediction: read it. It's full of interesting cases, builds intuition, and is a readable example of Bayesian thinking."

    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
 
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.