Congratulations!

Vector Databases for Embeddings with Pinecone

James Chapman

Curriculum Manager, DataCamp

Chapter 1 - Introduction to Pinecone

• Created an index → pc.create_index()
• Connect to it → pc.Index()
• Ingested vectors → index.upsert()

Chapter 2 - Pinecone Vector Manipulation in Python

 

Fetching

 

Querying

Chapter 3 - Performance Tuning and AI Applications

 

What's next?

 

Integrations

• Setting up your Knowledge Base for Amazon Bedrock
• Retrieval Augmentation in LangChain
• Hugging Face Inference Endpoints

 

Congratulations!

Vector Databases for Embeddings with Pinecone