Deploying a movie recommender system on Vertex AI

Now, let’s walk through an example of creating a movie recommendation system based on a collaborative filtering type model, deploying it on Vertex AI, and then querying it to get movie recommendations for specific users and movie genre types. The key steps are as follows:

1. Data preparation
2. Model design and training
3. Local model testing
4. Registering the model on Vertex AI
5. Deploying the model
6. Getting predictions

Note

The notebook for this exercise can be found at https://github.com/PacktPublishing/The-Definitive-Guide-to-Google-Vertex-AI/blob/main/Chapter15/Chp-15_Movie_Recommender.ipynb.

Dataset: To train the model, we will use the MovieLens dataset (F. Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4: 19:1–19:19. https://doi.org/10.1145/2827872).

The MovieLens dataset is one of...