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).

47
/ 100
Emerging

This project helps businesses or individuals understand and implement how to provide personalized movie recommendations to their users. You input user movie ratings, and the system outputs tailored movie suggestions. This is ideal for product managers, data scientists, or entrepreneurs looking to add a recommendation feature to a streaming service or entertainment platform.

100 stars. No commits in the last 6 months.

Use this if you want to see a working example of a movie recommendation system and learn how to build one using Apache Spark.

Not ideal if you are looking for a plug-and-play solution for instant integration without any development or data science involvement.

movie-streaming personalized-content recommendation-engines customer-engagement data-driven-features
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 22 / 25

How are scores calculated?

Stars

100

Forks

56

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Apr 17, 2023

Commits (30d)

0

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