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RAG: Vector Database to Store Document Embeddings

IntermediateGuided Project

Explore vector databases such as Chroma DB and Facebook AI Similarity Search (FAISS) in this guided project. You'll learn how to convert documents into vector embeddings, store them effectively, and perform similarity searches to retrieve relevant information. This project is ideal for anyone interested in understanding how to integrate machine learning techniques with database solutions for tasks such as recommendation systems and information retrieval.

Language

  • English

Topic

  • Artificial Intelligence

Enrollment Count

  • 82

Skills You Will Learn

  • Artificial Intelligence, Information Retrieval, NLP, Python, Vector Database, Vector Embeddings

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 30 minutes

Platform

  • SkillsNetwork

Last Update

  • March 17, 2026
About this Guided Project
Explore vector databases such as Chroma DB and FAISS in this guided project. You'll learn how to convert documents into vector embeddings, store them effectively, and perform similarity searches to retrieve relevant information. This project is ideal for anyone interested in understanding how to integrate machine learning techniques with database solutions for tasks like recommendation systems and information retrieval. Whether you're a data enthusiast or a developer, this project offers hands-on experience in integrating machine learning with advanced database solutions, enhancing your capabilities in recommendation systems and information retrieval. In just 30 minutes, you'll unlock the potential of scalable and accurate text data searches, ready to tackle complex challenges in the data landscape.

What you'll learn


After completing the project, you will be able to:

  • Prepare and preprocess documents for embeddings.
  • Generate embeddings using watsonx.ai's embedding model.
  • Store these embeddings in Chroma DB and FAISS.
  • Perform similarity searches to retrieve relevant documents based on new inquiries.


What you'll need


Before starting this guided project, you should have:

  • A basic understanding of Python programming.
  • Familiarity with machine learning concepts.
  • Access to a modern web browser such as Chrome, Edge, Firefox, Internet Explorer, or Safari for the best experience with the IBM Skills Network Labs environment, which comes with essential tools pre-installed.