Data Science Weekly Newsletter - Issue 212

Issue #212

Dec 14 2017

Editor Picks
  • What the SATs Taught Us about Finding the Perfect Fit
    On the Stitch Fix Algorithms team, we’ve always been in awe of what professional stylists are able to do, especially when it comes to knowing a customer’s size on sight. It’s a magical experience to walk into a suit shop, have the professional shopping assistant look you over and without taking a measurement say, “you’re probably a 38, let’s try this one,” and pull out a perfect-fitting jacket. While this sort of experience has been impossible with traditional eCommerce, at Stitch Fix we’re making it a reality...

A Message from this week's Sponsor:


Quick Question For You: Do you want a Data Science job?

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The course is broken down into three guides:
  1. Data Science Getting Started Guide. This guide shows you how to figure out the knowledge gaps that MUST be closed in order for you to become a data scientist quickly and effectively (as well as the ones you can ignore)

  2. Data Science Project Portfolio Guide. This guide teaches you how to start, structure, and develop your data science portfolio with the right goals and direction so that you are a hiring manager's dream candidate

  3. Data Science Resume Guide. This guide shows how to make your resume promote your best parts, what to leave out, how to tailor it to each job you want, as well as how to make your cover letter so good it can't be ignored!

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Data Science Articles & Videos

  • AIVA: AI Generated Music
    Did you like that orchestra performing AI-composed music at our NIPS2017 party last night? The AI is called AIVA, and her story is quite unique. AIVA taps into powerful AI technologies to create compositions for everything from advertisements to feature films with amazing originality and emotion...
  • Multivariate Map Collection
    Here is my attempt to collect examples of multivariate maps I’ve found and organize them into a loose categorization. Follow along, or dive into the references, to spur on your own investigations and inspirations!...
  • Learning from users faster using machine learning
    Consider this blog post a bit of a wacky experiment — I think the outcome is super interesting, and worth thinking more about..My idea is: create a model that predicts whether someone is going to purchase a widget given a lot of additional data. And instead of using the actual target metric (what fraction of people bought widgets) we use the predicted metric, using our machine learning model...
  • Deep Learning for NLP, advancements and trends in 2017
    In this article I will go through some advancements for NLP in 2017 that rely on DL techniques. I do not pretend to be exhaustive: it would simply be impossible given the vast amount of scientific papers, frameworks and tools available. I just want to share with you some of the works that I liked the most this year...
  • Who to follow in NIPS2017
    Interesting visualization of how much Twitter-based influence/mindshare people/organizations have on the field of AI right now...
  • Visual Domain Decathlon
    This taster challenge tests the ability of visual recognition algorithms to cope with (or take advantage of) many different visual domains...


  • Data Scientist - Farfetch - NYC

    As a fast-growing fashion e-commerce business and one of the world’s most valuable startups, harnessing the value of the data generated by our operations is critical to Farfetch’s future success and the Data Science teams are at the forefront of this effort.

    All of our work in Data Science is directed at building software solutions that enhance the marketing activity of the company by using Machine Learning and advanced statistical methods. This means understanding the customer, figuring out who they are, what they want and how to get their attention. Critically, we build systems that do this autonomously...

Training & Resources

  • TFGAN: A Lightweight Library for Generative Adversarial Networks
    In order to make GANs easier to experiment with, we’ve open sourced TFGAN, a lightweight library designed to make it easy to train and evaluate GANs. It provides the infrastructure to easily train a GAN, provides well-tested loss and evaluation metrics, and gives easy-to-use examples that highlight the expressiveness and flexibility of TFGAN...



  • Python Crash Course

    An insightful, revealing history of how mathematics transformed our world...
    Thorough introduction to programming with Python...

    "I have read multiple beginner guides to Python. I am currently up to chapter 11 in Python Crash Course. So far this is far and away my favorite Python programming book..."

    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. We just opened up booking for 2018 - grab a spot now; first come first served! Email us for more details - All the best, Hannah & Sebastian
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