Video course · 8 chapters · 36 min · certificate
Vector Embeddings Tutorial – Code Your Own AI Assistant with GPT-4 API + LangChain + NLP
Ania Kubow's freeCodeCamp tutorial on vector embeddings: what text embeddings are, cosine similarity and the king−man+woman=queen idea, where embeddings are used, generating them with OpenAI, why vector databases matter, setting up DataStax Astra DB, LangChain basics, and building a Python AI assistant that searches headlines by meaning.
What you'll learn
- Explain vector and text embeddings
- Measure similarity with cosine similarity
- Name common uses of embeddings
- Generate embeddings with the OpenAI API
- Store vectors in Astra DB
- Build a LangChain vector search assistant
Chapters
8 chapters · 36:23-
2:14
01Intro Members
Introduction to vector embeddings
Data as numbers.
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5:44
02Similarity Members
Text embeddings
Meaning in numbers.
-
3:07
03Uses Members
Uses of vector embeddings
Everywhere.
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3:32
04OpenAI Members
Generating embeddings with OpenAI
Create one.
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1:25
05Vector DB Members
Vectors and databases
Search by meaning.
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2:03
06Setup Members
Setting up the database
Astra DB.
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1:19
07LangChain Members
LangChain
Better LLM interactions.
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16:59
08Build Members
Building the AI assistant
Search by meaning.
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