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).
Topics
Explore related topics
Jump into the topic listings this repository belongs to.
Join the conversation
Reviews · Questions · Posts
Share what you know about movie-recommender-demo — write a review from your real experience, ask an implementation question, or publish a post about how you use it.
Share your experience
Write or update your review
Explain what worked, what broke down, and what another team should know before adopting movie-recommender-demo.
Project Q&A
Questions and answers
Browse implementation threads tied directly to snowch/movie-recommender-demo. Each question links through to the full answer page.
Be the first to ask how teams run movie-recommender-demo in production. Every question you post becomes a durable, searchable answer page other developers can find.
Ask the first questionRelated posts
Posts tagged with the same topics
These posts come from the same topic surface as this repo, so readers can move from project evaluation into practical writeups and migration notes without leaving context.
Share how your team uses movie-recommender-demo — a migration note, an architecture writeup, or a comparison. Your post reaches everyone browsing these same topics.
Write the first post