8th December 2014 in London There are 48 other SkillsCasts available from Scala eXchange 2014 Please log in to watch this conference skillscast. Users of Big (and not so Big) Data roughly divide into three groups, developers like us, traditional data analysts, and a hybrid called data scientists. The analysts prefer SQL, SAS, and similar, traditional tools. The scientists (mostly statisticians, re
Providing personalized recommendations is important to our online marketplace. It benefits both buyers and sellers: buyers are shown interesting products that they might not have found on their own, and products get more exposure beyond the seller’s own marketing efforts. In this post we review some of the methods we use for making recommendations at Etsy. The MapReduce implementations of all t
What you'll learn This course teaches you how to use Scalding (a domain specific language) built on Scala and Cascading to build distributed applications on Hadoop. The course also focuses on the data science aspect using Algebird, an abstract algebra library for Scala, to solve real-world sketching/streaming problems on distributed systems. You will learn how to reason about a variety of problems
Buy now, pay later (BNPL) methods, little-known less than a decade ago, now account for more than $300 billion in transactions worldwide. However, they tend to be priced at a premium, so our users wanted to know whether the financial benefits would offset the added costs. With that in mind, we ran an experiment to help Stripe businesses assess when and how to offer BNPLs.
We are often interested in finding users, hashtags and ads that are very similar to one another, so they may be recommended and shown to users and advertisers. To do this, we must consider many pairs of items, and evaluate how “similar” they are to one another. We call this the “all-pairs similarity” problem, sometimes known as a “similarity join.” We have developed a new efficient algorithm to so
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