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Data Science Weekly Newsletter
August 25, 2016

Editor's Picks

  • A Concise History of Neural Networks
    The idea of neural networks began unsurprisingly as a model of how neurons in the brain function, termed ‘connectionism’ and used connected circuits to simulate intelligent behaviour...
  • Self-driving Car Visualization and Gas Model
    More self-driving car modeling. Now with a sweet animation of the steering! We start work on the gas model, converting to categorical variables, but predicting "always drive forward" is too good for the model to overcome...

A Message From This Week's Sponsor

  • Want to use your Python skills to break into Data Science?

    In Springboard's Data Science Intensive Workshop - learn online with a personal mentor, build real-world data science projects and start participating in Kaggle competitions. Perfect for those with statistics and programming backgrounds. Spots for the next class (Aug 29th) are filling fast. Enroll now!

Data Science Articles & Videos

  • 3 Reasons Counting is the Hardest Thing in Data Science
    Counting is hard. You might be surprised to hear me say that, but it's true. As a data scientist, I've done it all - everything from simple regression analysis all the way to coding Hadoop MapReduce jobs that process hundreds of billions of data points each month. And, with all that experience, I've found that counting often involves far more time and effort...
  • Five great charts in 5 lines of R code each
    Sharon Machlis is a journalist with Computerworld, and to show other journalists how great R is for data visualization she shows them these five data visualizations, each of which can be created in 5 lines of R code or less...
  • The Trouble with Chernoff
    In 1973, applied statistician Herman Chernoff proposed one of the most strange and ingenious ideas in the history of information visualization – symbolizing data using faces...
  • The Data of Space
    Lost. In. Spaaaaaaace! Cosmology! Astrophysics! Astronauts! This week we talk with some amazing guests!...
  • An Introduction to Contextual Bandits
    In this post I discuss the Multi Armed Bandit problem and its applications to feed personalization. First, I will use a simple synthetic example to visualize arm selection in with bandit algorithms, I also evaluate the performance of some of the best known algorithms on a dataset for musical genre recommendations...
  • Full Resolution Image Compression with Recurrent Neural Networks
    This paper presents a set of full-resolution lossy image compression methods based on neural networks. Each of the architectures we describe can provide variable compression rates during deployment without requiring retraining of the network: each network need only be trained once...
  • 7 Ways To Be Driven Off A Data Cliff
    You can proudly tell all your friends that you are leading a modern data-driven team. Nothing can go wrong, right? Incorrect. If you don’t pay attention, data can drive you off a cliff. This article discusses seven of the ways this can happen. Read on to ensure it doesn’t happen to you...


  • Data Scientist - Indeed - Austin, TX
    As a Data Scientist at Indeed your role is to follow the data. Analyze, visualize, and model job search related data. You will build and implement machine learning models to make timely decisions. You will have access to unparalleled resources within Indeed to grow and develop both personally and professionally. We are looking for a mixture between a statistician, scientist, machine learning expert and engineer: someone who has passion for building and improving Internet-scale products informed by data. The ideal candidate understands human behavior and knows what to look for in the data...

Training & Resources

  • How Convolutional Neural Networks Work
    What’s especially cool about them is that they are easy to understand, at least when you break them down into their basic parts. I’ll walk you through it...


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