Web Picks (week of 22 August 2016)

Every two weeks, we find the most interesting data science links from around the web and collect them in Data Science Briefings, the DataMiningApps newsletter. Subscribe now for free if you want to be the first to get up to speed on interesting resources.

  • 98 personal data points that Facebook uses to target ads to you
    “Say you’re scrolling through your Facebook Newsfeed and you encounter an ad so eerily well-suited, it seems someone has possibly read your brain. Whatever the subject, you’ve seen ads like this. You’ve wondered — maybe worried — how they found their way to you.”
  • What’s Next for Artificial Intelligence
    The best minds in the business—Yann LeCun of Facebook, Luke Nosek of the Founders Fund, Nick Bostrom of Oxford University and Andrew Ng of Baidu—on what life will look like in the age of the machines.
  • Forget Python vs. R: how they can work together
    “A few weeks ago I had the opportunity to speak at SciPy about how we use both Python and R at Civis. Why go all the way to a Python conference to talk about R? Was I fanning the flames of yet another Python vs R language war? No! We happily work in both languages—not only for our daily work solving data science problems, but also in writing tools.”
  • AI’s Language Problem
    Machines that truly understand language would be incredibly useful. But we don’t know how to build them.
  • Goods: organizing Google’s datasets
    Great point: “You can (try and) build a data cathedral. Or you can build a data bazaar. By data cathedral I’m referring to a centralised Enterprise Data Management solution that everyone in the company buys into and pays homage to, making a pilgrimage to the EDM every time they want to publish or retrieve a dataset. A data bazaar on the other hand abandons premeditated centralised control.”
  • Rodeo for Windows is here!
    From yhat: “Earlier this summer we released version 2.0 of our Python IDE, Rodeo, for Mac & Linux. After lots of code rewriting and TLC, we are excited to finally officially support Windows with version 2.1.”
  • Deep Deterministic Policy Gradients in TensorFlow
    Google DeepMind has devised a solid algorithm for tackling the continuous action space problem. Building off the prior work of on Deterministic Policy Gradients, they have produced a policy-gradient actor-critic algorithm called Deep Deterministic Policy Gradients (DDPG) that is off-policy and model-free, and that uses some of the deep learning tricks that were introduced along with Deep Q-Networks.
  • Apple acquires Turi
    Machine learning and artificial intelligence startup Turi has been acquired by Apple in a deal characterized as a blockbuster exit for the Seattle-based company, formerly known as Dato and GraphLab, GeekWire has learned.
  • Building a Data Pipeline with Airflow
    “In this blog post I’ll setup a data pipeline that takes currency exchange rates, stores them in PostgreSQL and then caches the latest exchange rates in Redis.”