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Sean Owen and Recommendations at Scale

We recently hosted a BigData.be meetup on Recommendations at Scale using Mahout. We invited Sean Owen – the original contributor of the recommender algorithms in Apache Mahout to introduce our audience to the concepts (and difficulties) of machine learning at scale, more specifically collaborative filtering and the alternate least square algorithm. You will find the presentation video and some photo impressions underneath:

Lily 2.0 will ship with a built-in machine learning and recommendation engine. Using Lily, you are now able to manage tons of data and have them indexed and made searchable in real-time. With Lily 2.0, real-time machine learning will then no longer be reserved for the likes of Amazon and LinkedIn, but instead become a real possibility for any organisation.

Enjoy the video of Sean’s presentation!

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