Data Science Weekly Newsletter - Issue 101

Issue #101

October 29 2015

Editor Picks
 
  • What a Deep Neural Network thinks about your #selfie
    Convolutional Neural Networks are great: they recognize things, places and people in your personal photos, signs, people and lights in self-driving cars, crops, forests and traffic in aerial imagery, various anomalies in medical images and all kinds of other useful things. But once in a while these powerful visual recognition models can also be warped for distraction, fun and amusement. In this fun experiment we're going to do just that...
  • Estimating Delivery Times at Postmates: Practical Machine Learning
    With the release of Postmates 3.0, I had the opportunity to apply Machine Learning tools. I would like to share with you some insights I gained from the development process for Estimated Delivery Time, and hopefully illustrate how powerful the proper application of some simple and accessible Machine Learning techniques can be when applied to the right problem...
 
 

A Message from this week's Sponsor:

 


 

Data Science Articles & Videos

 
  • The First Step To Take When Looking For A Data Science Job
    You have decided to look for a new job in the data science field and are finding it very hard. As someone new to the field, it all looks very chaotic and confusing to you. You want to find the right job for you and don't want to waste your time trying to apply to every single company advertising a job. Given a limited amount of time and wanting to find the right opportunity, where do you start?...
  • Generating Captions: Describing Videos with Neural Networks
    Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. Recent advances are starting to enable machines to describe image with sentences. This experiment uses neural networks to automatically describe the content of videos...
  • Data Science & Analytics at Birchbox
    Liz Crawford, CTO of Birchbox, presented at Data Driven NYC in October 2015. She gave a behind-the-scenes look at Birchbox's Data Science & Analytics practice...
  • Getting Uncomfortable with Data
    But it’s a rare data scientist who challenges our core values and exhorts us to get uncomfortable with the fundamental tools of our trade. A few days ago, Cloudera hosted Wrangle, a conference for and by data scientists. The talks were consistently excellent, filled with war stories from some of the industry’s top companies in the field. But the talk that stood out was Clare Corthell’s talk on “AI Design for Humans”. She made several points that I hope every data scientist internalizes...
  • NFL Coach Firing Model: Week 8
    Last year, we implemented a coaching firing model to assign a probability that a front office would actively let its head coach go by year’s end that is designed to answer this question. Despite the fact that we felt good about our inputs, we worried that we might be overfitting a bit, and so we decided to use several methods of cross-validation to evaluate our model. After testing various models using leave-one-out and 10-fold cross-validation methods, we found nine variables to be explanatory of firing odds...
  • Interview with a Data Scientist: Trey Causey
    Trey Causey is a blogger with experience as a professional data scientist in sports analytics and e-commerce. He’s got some fantastic views about the state of the industry...
 
 

Jobs

 
  • Data Scientist - Shopkick - Redwood City, CA

    Shopkick is looking for a passionate Data Scientist that wants to solve incredibly hard problems and help create the future of real world shopping! You will be an integral member of the team working cross functionally across the various divisions at shopkick. You will be analyzing huge amounts of complex data collected by our smartphone app and ibeacons relating to consumers shopping trends at major brand store locations. In doing so, deriving highly scalable retail oriented solutions, generating meaningful reports and metrics to be acted upon by the Executives, further influencing the direction of the company through you awesome contribution. Of course, you’ll also be testing out new and great ideas!...
 
 

Training & Resources

 
  • An Engineer’s Guide to GEMM
    I’ve spent most of the last couple of years worrying about the GEMM function because it’s the heart of deep learning calculations. The trouble is, I’m not very good at matrix math! The best way I know to fix something in my own mind is to try to explain it to somebody else, so here are my notes...
 
 

Books

 

  • Now You See It: Simple Visualization Techniques for Quantitative Analysis

    Teaches simple, practical means to explore and analyze quantitative data...

    "As someone who's done over two decades of research and development on visualization technology, I highly recommend "Now You See It" for everybody - novice to expert. Stephen Few explains visual analysis clearly and conversationally. His examples are accessible, appropriate, and beautiful..."

    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.