Big data

11 Jun 2014
Sergey Feldman

Personalization with Contextual Bandits

This is the third in a series of three blog posts about bandits for recommendation systems. In the first and second blog posts we covered the bandit problem, and some ways to solve it.  But in doing so, we ignored two critical challenges to dishing out recommendations in the real world. They are: 1. What if you... View Article

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05 Jun 2014
Sergey Feldman

Recommendations with Thompson Sampling

This is the second in a series of three blog posts on bandits for recommendation systems. If you read the last blog post, you should now have a good idea of the challenges in building a good algorithm for dishing out recommendations in the bandit setting.  The most important challenge is to balance exploitation with... View Article

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02 Jun 2014
Sergey Feldman

Bandits for Recommendation Systems

This is the first in a series of three blog posts on bandits for recommendation systems.  In this blog post, we will discuss the bandit problem and how it relates to online recommender systems.  Then, we'll cover some classic algorithms and see how well they do in simulation. A common problem for internet-based companies is:... View Article

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09 May 2014
Gaurav Tungatkar

Smart API Publishing using Circuit Breakers

Smart API Publishing using Circuit Breakers This is the first in a series of blog posts about how we have architected a scalable and distributed API platform for retailers. Introduction DataMesh is our self-service flexible platform that enables rapid application development, be it the creation of new recommendation algorithms, social media integrations or enablement of... View Article

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