Introduction to Vector Embeddings and Weaviate - Part 1

Introduction to Vector Embeddings and Weaviate - Part 1

Data Science Dojo via YouTube Direct link

36:56 - Comparing Open-Source vs. Closed-Source Models

9 of 12

9 of 12

36:56 - Comparing Open-Source vs. Closed-Source Models

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Introduction to Vector Embeddings and Weaviate - Part 1

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  1. 1 0:00 - What are Vectors and Vector Embeddings?
  2. 2 2:37 - Mathematical Properties of Vector Embeddings
  3. 3 4:42 - RGB Color Codes as Vectors
  4. 4 8:00 - Word2Vec: The First Embedding Model
  5. 5 12:59 - Transformer Models and the Attention Mechanism
  6. 6 17:55 - Choosing an Embedding Model
  7. 7 25:10 - Demo: Generating and Storing Embeddings in Weaviate
  8. 8 32:15 - Demo: Using OpenAI for Embeddings
  9. 9 36:56 - Comparing Open-Source vs. Closed-Source Models
  10. 10 39:06 - Case Study: Snowflake Arctic Embed 2.0
  11. 11 46:10 - Benchmarks and Model Performance Considerations
  12. 12 44:01 - Live Q&A Session

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