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SkillsCast

Building an Open Source movie recommender using Apache Spark and IBM Cloud Data Services

23rd March 2017 in London at CodeNode

There are 1 other SkillsCast available from Understanding key machine learning algorithms

In this session, we provide a high level introduction to Collaborative Filtering using Apache Spark's ALS (alternating least squares) machine learning algorithm. We then walk through an example collaborative filtering web application for movie recommendations. The application is built using services on the IBM Cloud: Data Science Experience (DSX), Spark as a Service, Cloudant, Compose Redis and Bluemix. We briefly cover each of these services and the properties they bring to the application architecture.

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Building an Open Source movie recommender using Apache Spark and IBM Cloud Data Services

Chris Snow

Chris Snow is an IBM data and application architect who loves helping customers with their data architectures. He is currently focused on IBM Cloud Data Services and emerging technologies such as big data streaming architectures.

SkillsCast

In this session, we provide a high level introduction to Collaborative Filtering using Apache Spark's ALS (alternating least squares) machine learning algorithm. We then walk through an example collaborative filtering web application for movie recommendations. The application is built using services on the IBM Cloud: Data Science Experience (DSX), Spark as a Service, Cloudant, Compose Redis and Bluemix. We briefly cover each of these services and the properties they bring to the application architecture.

Thanks to our sponsors

About the Speaker

Building an Open Source movie recommender using Apache Spark and IBM Cloud Data Services

Chris Snow

Chris Snow is an IBM data and application architect who loves helping customers with their data architectures. He is currently focused on IBM Cloud Data Services and emerging technologies such as big data streaming architectures.