GitHub / snowch / movie-recommender-demo

This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to topic where they are consumed by a spark streaming job running on IBM BigInsights (hadoop).

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/snowch%2Fmovie-recommender-demo

Topics: alternating-least-squares, biginsights, bluemix, bokeh, cloudant, collaborative-filtering, dsx, hadoop, hive, ibm-biginsights, ibm-bluemix, jupyter-notebook, kafka, machine-learning, messagehub, notebook, python-flask-application, redis, spark, spark-streaming

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