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Building a recommendation engine with Python and Neo4j


PyData London 2016

In this session Mark will show how to build a recommendation engine using Neo4j and Python.

Our solution will be a hybrid which makes uses of both content based and collaborative filtering to come up with multi layered recommendations that take different datasets into account e.g. we'll combine data from the and twitter APIs.

We'll evolve the solution from scratch and look at the decisions we make along the way in terms of modelling and coming up with factors that might lead to better recommendations for the end user.


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