Data Science Weekly Newsletter - Issue 220

Issue #220

Feb 8 2018

Editor Picks
 
  • 100,000 Happy Moments
    What makes people happy? A huge database is making it possible to discern the answer at last...
 
 

A Message from this week's Sponsor:

 

 
Become an Apache Spark expert with The Data Scientist's Guide to Apache Spark™

Looking to dive deeper into cutting edge machine learning use cases in Apache Spark? To successfully use Spark’s advanced analytics capabilities, check out The Data Scientist’s Guide to Apache Spark by Databricks’ Matei Zaharia (creator of Spark). Learn the fundamentals of advanced analytics and receive a crash course in machine learning. Get a deep dive on MLlib, Spark’s primary machine learning package and discover how to implement recommendation engines and deep learning algorithms.

 
 
 

Data Science Articles & Videos

 
  • A Code of Ethics for Data Science
    2.5 quintillion bytes of data are created every day. It’s created by you when you’re commute to work or school, when you’re shopping, when you get a medical treatment, and even when you’re sleeping. It’s created by you, your neighbors, and everyone around you. So, how do we ensure it’s used ethically?...
  • Open Access at The Met: Animating Artworks in the Collection
    I am an independent web and educational software developer with an AB in physics as well as experience coding interactive museum exhibitions. I have always been interested in the creative coding movement, but I felt I was missing the right inspiration to contribute. When The Met released its collection of hundreds of thousands of images of public-domain works in early 2017, I realized I could take my background in physics and software development and fuse it with my lifelong love of art to create projects using these Open Access images...
  • Getting Linked In to Data Science with Dr. Igor Perisic
    Today, we welcome a special guest to the podcast. Dr. Igor Perisic is the Vice President of Engineering and Chief Data Officer at LinkedIn, the social network for business and employment. On this episode, Dr. Perisic talks about the key attributes of a data scientist, how AI and machine learning are helping personalize member experiences, why we should all be big open source fans, and how LinkedIn is partnering with other researchers through their innovative Economic Graph program to “create economic opportunity for every member of the global workforce.”...
  • Sampling Generative Networks
    We introduce several techniques for sampling and visualizing the latent spaces of generative models. Replacing linear interpolation with spherical linear interpolation prevents diverging from a model's prior distribution and produces sharper samples...

 

Jobs

 
  • Data Scientist - Raise Marketplace - New York or Chicago
    Raise, a leading retail payments company and the world’s largest gift card marketplace, connects consumers to buy discounted gift cards or sell their unwanted cards for cash.

    Raise Data Scientists are a critical component of the cross-functional squads that make up the Raise Technology organization, reporting directly to the Director of Analytics. As a Data Scientist at Raise, you are responsible for delivering data informed insights to a given Technology Squad, while providing expertise in data collection, experiment design, and interpretation of statistics. You will be responsible for creating, analyzing and optimizing reports that help to drive critical product decisions...
 
 

Training & Resources

 
  • Sum A List Of TensorFlow Tensors
    Learn how to sum a list of TensorFlow Tensors using the TensorFlow add_n operation so that you can add more than two TensorFlow Tensors together at the same time...
  • DMLab-30
    DMLab-30 is a set of environments designed for DeepMind Lab. These environments enable a researcher to develop agents for a large spectrum of interesting tasks either individually or in a multi-task setting. We have released 28 levels. Two remaining levels will be added soon...
 
 

Books

 

  • Seven Databases in Seven Weeks:
    A Guide to Modern Databases and the NoSQL Movement


    "A book that tries to cover multiple database is a risky endeavor, a book that also provides hands on on each is even riskier but if implemented well leads to a great package. I loved the specific exercises the authors covered. A must read for all big data architects who don’t shy away from coding..."


    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
 
 
P.S., Want to reach our audience / fellow readers? Consider sponsoring - grab a spot now; first come first served! All the best, Hannah & Sebastian
 
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