Skip to content

Leverage vector databases to swiftly construct a diverse range of applications through "Building Applications with Vector Databases" course!

Notifications You must be signed in to change notification settings

ksm26/Building-Applications-with-Vector-Databases

Repository files navigation

πŸ’» Welcome to the "Building Applications with Vector Databases" course! This course, instructed by Tim Tully, Board member at Pinecone, will teach you how to leverage vector databases to build a variety of applications quickly and efficiently.

Course Website: πŸ“šdeeplearning.ai

Course Summary

In this course, you will explore the implementation of six applications using vector databases. Here's what you can expect to learn and experience:

  1. πŸ” Semantic Search: Create a search tool that focuses on the meaning of content for efficient text-based searches on a user Q/A dataset.

  1. βš™οΈ Retrieval Augmented Generation (RAG): Enhance your LLM applications by incorporating content from external sources like the Wikipedia dataset.

  1. πŸ›’ Recommender System: Develop a system that combines semantic search and RAG to recommend topics, demonstrated with a news article dataset.

  1. 🌐 Hybrid Search: Build an application for multimodal search using both images and descriptive text, demonstrated with an eCommerce dataset.

  1. 😊 Facial Similarity: Create an app to compare facial features using a database of public figures to determine likeness.

  1. 🚨 Anomaly Detection: Build an app to identify unusual patterns in network communication logs.

Key Points

  • πŸ›  Learn to create six exciting applications of vector databases and implement them using Pinecone.
  • πŸ“Έ Build a hybrid search app that combines both text and images for improved multimodal search results.
  • πŸ˜ƒ Learn how to build an app that measures and ranks facial similarity.

About the Instructor

🌟 Tim Tully is a board member at Pinecone and brings extensive expertise in vector databases to guide you through building various applications.

πŸ”— To enroll in the course or for further information, visit deeplearning.ai.