How Airbnb uses Machine Learning to Detect Host Preferences
At Airbnb we seek to match people who are looking for accommodation — guests — with those looking to rent out their place — hosts. Guests reach out to hosts whose listings they wish to stay in, however a match succeeds only if the host also wants to accommodate the guest. I first heard about Airbnb in 2012 from a friend. He offered his nice apartment on the site when he traveled to see his family
Explore career opportunities at Pinterest
Contractor roles While our Careers site currently focuses on direct employment roles with Pinterest, we also offer temporary (contractor) assignments through our trusted third-party staffing firms. Job postings for contractor assignments on some of the most popular professional networking sites and job boards will clearly indicate the assignment duration, the staffing firm that will be the direct
Distributed Time Travel for Feature Generation
We want to make it easy for Netflix members to find great content to fulfill their unique tastes. To do this, we follow a data-driven algorithmic approach based on machine learning, which we have described in past posts and other publications. We aspire to a day when anyone can sit down, turn on Netflix, and the absolute best content for them will automatically start playing. While we are still wa
Hivemall talk@Hadoop summit 2014, San Jose
This document discusses Hivemall, a scalable machine learning library for Apache Hive. It provides concise summaries of machine learning algorithms as user-defined functions that can run on large datasets in Hive. The document outlines the motivation for Hivemall, what algorithms it supports, how to use it to perform tasks like data preparation, training models, and prediction, and how it handles
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https://prantik.github.io/docs/lasta14.pdf
Real-time Recommendations using Spark Comcast Labs
