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Data Science Weekly Newsletter
Issue
114
January 28, 2016

Editor's Picks

  • Owen Zhang - "How I Became a Data Scientist"
    Owen Zhang is ranked #1 on the Kaggle leaderboard out of a community of 200,000 data scientists. This talk describes how he transitioned from a software developer in a corporate IT to a data scientist in a startup, with a focus on the practical lessons learned...



A Message From This Week's Sponsor


 
  • Is Your Resume As Good As You Are?

    You've done the hard work and are ready to get your dream Data Science job. As soon as you apply, the only thing you'll be judged on is your resume. Hundreds of others are applying to the same jobs - don't let your resume sabotage you! You need to make a Hiring Manager want you. Learn how and set yourself up for success with this actionable 5 day email course on How to Read a Hiring Manager’s Mind. Enroll for free right now!


Data Science Articles & Videos

  • Eli Pariser on the Ethics of Algorithmic Filtering
    In 2011, Eli Pariser, CEO of Upworthy, wrote the first monograph about the risks algorithmic filtering poses to citizenship and society. We (FastForwardLabs) recently interviewed Pariser to see how his thinking has evolved in light of recent algorithmic progress...
  • The Rise of the Artificaially Intelligent Hedge Fund
    Last week, Ben Goertzel and his company, Aidyia, turned on a hedge fund that makes all stock trades using artificial intelligence—no human intervention required. “If we all die,” says Goertzel, a longtime AI guru and the company’s chief scientist, “it would keep trading.”...
  • Pixel Recurrent Neural Networks
    Modeling the distribution of natural images is a landmark problem in unsupervised learning. This task requires an image model that is at once expressive, tractable and scalable. We present a deep neural network that sequentially predicts the pixels in an image along the two spatial dimensions...
  • Analyzing 50k fonts using deep neural networks
    For some reason I decided one night I wanted to get a bunch of fonts. A lot of them. An hour later I had a bunch of scrapy scripts pulling down fonts and a few days later I had more than 50k fonts on my computer ... Now, let’s train a neural network that generates characters!...
  • 5 Reasons Kaggle Projects Won't Help Your Data Science Resume
    If you're starting out building your Data Science credentials you've probably often heard the advice "do a Kaggle project". And, those folks are right, its a great way to start to get your hands dirty, playing with data and different techniques. However, when it comes to what to put on your resume to showcase your project work, don't rely on Kaggle as evidence of your commitment or credentials. Here's why...



Jobs

  • Data Analyst - Patreon - San Francisco
    Patreon is the best way for creators to receive recurring funding directly from their fans. Everyone in the Patreon family is deeply invested in the mission of paying creators and empowering the emerging creative class. As a member of our growing Data Science team, you will analyze key metrics to answer big questions about our users and usage, inform product strategy and overall company strategy with data-driven research, and help us build a culture of data-driven decision making at Patreon...
    Learn more about the role and get some advice for your Data Science resume, in our interview with the Hiring Manager, Carlos Cabrera...


Training & Resources

  • Understanding Convolutional Neural Networks for NLP
    In this post I’ll try to summarize what CNNs are, and how they’re used in NLP. The intuitions behind CNNs are somewhat easier to understand for the Computer Vision use case, so I’ll start there, and then slowly move towards NLP...


Books


  • How to Measure Anything: Finding the Value of "Intangibles" in Business Explanation of how to measure those things in your own business that, until now, you may have considered "immeasurable"
    "An excellent read. It could be summed up as a "basic statistics for business" book, although it definitely goes beyond that in many aspects...."... For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page...


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