Introduction to Embeddings, Vector Databases, and Search

10 videos • 1,048 views • by Data Science Dojo This video series provides a comprehensive exploration of topics related to vector search. It covers an overview of embeddings, how vector search functions, filtering methods, vector stores, best practices, and concludes with practical notebook demonstrations using Pinecone and Weaviate.
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LLM Module 2 - Embeddings, Vector Databases, and Search | 2.2 Module Overview
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LLM Module 2 - Embeddings, Vector Databases, and Search | 2.3 How does Vector Search work
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LLM Module 2 - Embeddings, Vector Databases, and Search | 2.4 Filtering
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LLM Module 2 - Embeddings, Vector Databases, and Search | 2.5 Vector Stores
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5
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.6 Best Practices
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LLM Module 2 - Embeddings, Vector Databases, and Search | 2.7 Summary
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7
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.1 Notebook Demo Part 1
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LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.2 Notebook Demo Part 2
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9
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.9 Notebook Demo Pinecone (Optional)
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10
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.10 Notebook Demo Weaviate (Optional)
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