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Data Science Weekly Newsletter
March 30, 2017

Editor's Picks

  • I Took The AI Class Facebookers Are Literally Sprinting To Get Into
    Facebook isn’t just trying to beef its central AI lab. It’s hoping to spread these skills across the company. Deep learning isn’t a niche pursuit. It’s a general technology that can potentially change any part of Facebook, from Messenger to the company’s central advertising engine...

A Message From This Week's Sponsor

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Data Science Articles & Videos

  • Data Science Case Study: Turo's Dynamic Pricing and Recommender Engine
    Much like AirBNB revolutionized the hotel industry, Turo is transforming the car rental industry, one adventure at a time. Early on, the Turo team recognized the importance of data, and began capturing and storing information on how users navigated the site to lend and borrow vehicles in a central Amazon Redshift cluster...
  • In Defense of Simplicity, A Data Visualization Journey
    The last 8–9 years of my career have been focused on Data Visualization, which has given me plenty of time to develop a philosophy or two about my approach to this field. I say two, but I really mean about half a dozen of semi-distraught career-crisis generating moments (that lasted weeks or months) questioning what it is I want out of this field, whether what I am doing is the “right thing” and whether I should be doing something else...


  • 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

  • Pandas & Seaborn - A guide to handle & visualize data elegantly
    Up next you’ll find an overview of Pandas, a Python library which is old but gold and a must-know if you’re attempting to do any work with data while living in the Python world, and a glance of Seaborn, a Python library for making statistical visualizations. From our experience, they complement each other really well, and are worth learning together. We hope this post serves as a first guide for diving into them and kickstart your data handling & visualization journey...
  • Machine Learning in Python
    Use this free curriculum to build a strong foundation in Machine Learning, with concise yet rigorous and hands-on Python tutorials...
  • Making Dynamic Scales and Axes
    Intermediate level D3.js tutorial covering how to make scales and axis dynamic using Dynamic Data and the Update Data Function...


  • Linear Algebra and Its Applications
    "One of the best college textbooks ever! If I needed to miss a lecture, the book taught me everything I needed to know. I had no linear algebra background beforehand, and the book was very clear and easy to understand. Awesome for independent study."...

    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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