Build a movie recommendation app with Tensorflow and pgvector

Learn how to create a movie recommendation web app, using PostgreSQL® and pgvector. This workshop is 2 hours long with a short break in the middle.

When: Thursday June 13, 2024

  • 9am PDT | 12noon EDT | 6pm CEST

Secure your spot

What's in the Workshop Recipe?

We'll work together to build a movie recommendation system from start to finish, utilizing NodeJS, TensorFlow, and PostgreSQL’s extension pgvector. We'll guide you through the process of creating the vector embeddings using TensorFlow right on your laptop. Additionally, we'll leverage pg-promise to efficiently handle bulk row inserts, and we'll explore the usage of Next.js for a full-stack project. By the end of the workshop, you'll have a fully functional project that generates movie recommendations.

This workshop is particularly useful for those who are intrigued by contextual search and usage of AI, but might find themselves overwhelmed by the complexities of getting started.

Related resource in our developer center: TensorFlow, PostgreSQL®, pgvector & Next.js: building a movie recommender

Prepare for a Brain Upgrade

You will learn:

  • How to turn a movie plot into an embedding using TensorFlow
  • How to setup pgvector in PostgreSQL
  • How to import movie data into PostgreSQL, with embeddings for the plot descriptions
  • How to search for closest matching plots to a query
  • How to create a web app with Next.js
  • And finally, how to make it look nice as well!


You’ll also need

  • An Aiven account, using our free trial

We will lead you through setting that up in the workshop, if you don’t already have one.

Workshop host

Celeste Horgan
Celeste Horgan

Developer Educator, Aiven

Celeste is a Developer Educator at Aiven, where she focuses on bringing delightful, and creative content to Aiven’s tens of thousands of users. In previous roles, she’s acted as a documentation partner and advisor to the CNCF’s portfolio of open source projects, as an approver and Code of Conduct Committee member in the Kubernetes open source project, and as a team lead in documentation teams across a number of companies. In 2020 she founded the Inclusive Naming Initiative. Her work has been featured in the New York Times, and she presents frequently for global leaders in open source projects about documentation best practices.

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