Name: Machine learning: A recommender system in kdb+/q with MovieLens dataset
Start: 2017-01-19T18:30:00-05:00
End: 2017-01-19T20:00:00-05:00
Location: 1010Data

Nick Psaris, author of "Q-Tips, Fast, Scalable and Maintainable Kdb+," will use q to generate movie recommendations using a few different 'collaborative filtering' techniques on the MovieLens dataset: cosine similarity, singular value decomposition, and regularized gradient descent.

To make it more interesting, Nick will collect attendees favorite and least favorite movies so he can load their preferences for the demo. You can make your nominations here in the comment section, or send them to kxcommunity@kx.com .

Abby G.

KX Meetup New York

Technology

Data Visualization

Big Data

NoSQL

Operational Intelligence

Machine Learning

Blockchain

Internet of Things (IOT)

Predictive Analytics

kdb+

Business Intelligence

Cloud Computing

Streaming Analytics

In-Memory Computing

Time Series Analysis

Machine learning: A recommender system in kdb+/q with MovieLens dataset

1010Data

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KX Meetup New York

Machine learning: A recommender system in kdb+/q with MovieLens dataset

KX Meetup New York

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