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Data Science Weekly Newsletter
Issue
13
February 20, 2014

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Editor's Picks

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  • Flappy Bird hack using Reinforcement Learning
    This is a hack for the popular game, Flappy Bird. After playing the game a few times, I saw the opportunity to practice my machine learning skills and try and get Flappy Bird to learn how to play the game by itself...
  • A Billion Rows per Second: Metaprogramming Python for Big Data
    Ville Tuulos, Principle Engineer at AdRoll, demonstrates how they use Python to squeeze every bit of performance out of a single high-end server. They manage it with Numba, a new NumPy aware dynamic Python compiler based on LLVM. Find out more in this informative talk from the SF Python Meetup...

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Data Science Articles & Videos

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  • The Billion Dollar AI Castle in the Air
    High tech companies (e.g., Microsoft, Google, FaceBook, Netflix, Intel, Amazon, etc.) are pouring billions of dollars into a branch of artificial intelligence called machine learning. Below, I argue that, in spite of their initial successes, current approaches to machine learning will fail primarily because this is not the way the brain works...
  • This Algorithm can Predict a Revolution
    For students of international conflict, 2013 provided plenty to examine. There was civil war in Syria, ethnic violence in China, and riots to the point of revolution in the Ukraine. For those working at Duke University’s Ward Lab, all specialists in predicting conflict, the year looks like a betting sheet, full of predictions that worked and others that didn’t pan out...
  • How to Speed up a Python Program 114,000 times
    Optimizations are one thing -- making a serious data collection program run 114,000 times faster is another thing entirely. Leaning on 30+ years of programming experience, David Schachter goes over all the optimizations he made to his (secret) company's data-collecting program to get such massive performance gains. In doing so, he might be able to teach you a thing or two about optimizing a python program...
  • Cray Discovers a Viable Approach to Hadoop in Big Data Science
    Hadoop is certainly well known as a general framework for Big Data analytics but many have questioned whether it is suited for Scientific Big Data. We caught up with Mike Boros, Hadoop Product Manager at Cray, to learn about the company’s solution for this quandary...
  • How does LinkedIn's Recommendation System work?
    Ever since I studied Machine Learning and Data Mining at Stanford 3 years ago, I have been enamored by the idea that it is now possible to write programs that can sift through TBS of data to recommend useful things. So here I am with my colleague Adil Aijaz, for a talk on some of the lessons we learnt and challenges we faced in building large-scale recommender system...
  • Spectral Clustering: Intuition and Implementation
    Clustering is an important task that pertains to many areas. Spectral clustering is one clustering method. We will present some intuition on what it is, then go into a high level overview of the algorithm with experimental results, along with psuedocode and implementation detail This is meant to be a lighthearted overview...

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Jobs

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  • Data Scientist/Quantitative Analyst, YouTube - San Bruno CA
    At YouTube, data drives the way we make decisions. As a Data Scientist, you should be experienced with and passionate about using data to drive strategy and product recommendations. You are able to both engage with senior leaders to design well-constructed analyses and work cross-functionally with analysts, product managers and engineers to effectively deliver actionable results. The ideal candidate is an independent, solution-oriented thinker with a strong background processing huge data sets, applying analytical rigor and statistical methods, and driving toward insights and solutions...

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Training & Resources

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