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Data Science Weekly Newsletter
April 20, 2017

Editor's Picks

A Message From This Week's Sponsor

  • [WHITEPAPER] Applied Data Science by Yhat, Inc.

    This is a white paper about data science teams and how companies apply their insights to the real world. You’ll learn how successful data science teams are composed and operate and which tools and technologies they are using.

Data Science Articles & Videos

  • A Neural Parametric Singing Synthesizer
    We present a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of pitch and timbre. This allows conveniently modifying pitch to match any target melody, facilitates training on more modest dataset sizes, and significantly reduces training and generation times...
  • NBA Foul Calls and Bayesian Item Response Theory
    Since 2015, the NBA has released a report reviewing every call and non-call in the final two minutes of every NBA game where the teams were separated by five points or less with two minutes remaining. The NBA is certainly marketed as a star-centric league, so this data set presents a fantastic opportunity to understand the extent to which the players involved in a decision impact whether or not a foul is called...
  • Predicting Churn without Machine Learning
    In this post I will describe a way of predicting churn based on customers' inactivity profile that I've applied in various client engagements. Without using machine learning algorithms, the model delivers an interpretable prediction of churn that gives a fairly accurate insight into the customers leaving the base...
  • Gender Roles with Text Mining and N-grams
    Today is the one year anniversary of the janeaustenr package’s appearance on CRAN, its cranniversary, if you will. I think it’s time for more Jane Austen here on my blog....
  • Stitchfix- The Making of the Tour, Part 2: Simulations
    In our first installment of this Making of the Tour series we gave a general overview of our development process and our scrollytelling code structure. Now we get to dig into some details. In this post, we’ll talk about some simulation-powered animations, provide some cleaned-up code that you can use, and discuss these animations’ genesis and utility for visualizing abstract systems and algorithms or for visualizing real historical data and projected futures...


  • Senior Data Analyst - VSCO - Oakland, CA
    VSCO is a leading creative platform with a monthly audience of over 45 million and growing.
    We are looking for a Senior Data Analyst to build data at VSCO from the ground up. You will design our data model for user behavior and content impression, and will mine the data to find insights that will influence the product roadmap. Expect to get your hands dirty with Redshift, Spark, and data visualization tools under the guidance of our Director of Data Science....

Training & Resources

  • Caffe2 - New release from Facebook
    Caffe2 aims to provide an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2's cross-platform libraries...
  • Numenta Anomaly Benchmark for Streaming Anomaly Detection
    With sensors invading our everyday lives, we are seeing an exponential increase in the availability of streaming, time-series data. Finding anomalies or unusual behavior in this data can be extremely valuable, but doing it reliably is quite difficult. There are dozens of anomaly detection algorithms in the literature but it is almost impossible to evaluate them for streaming because existing benchmarks focus on non-streaming batch data. We created the open source Numenta Anomaly Benchmark (NAB) to fill this hole...


  • Bayes Theorem: A Visual Introduction For Beginners
    "This book takes what can be a daunting and complex subject and breaks it down with a series of easy to follow examples which buildup to deliver a great overall explanation of how to use Bayes Theorem for basic analysis and even off-the-cuff critical thinking"......
    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page...
Looking to hire a Data Scientist? Find an awesome one among our readers! Email us for details on how to post your job :) - All the best, Hannah & Sebastian

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