Stress Testing Qdrant - Semantic Search with 90,000 Vectors - Lightning Fast Search Microservice

Stress Testing Qdrant - Semantic Search with 90,000 Vectors - Lightning Fast Search Microservice

David Shapiro ~ AI via YouTube Direct link

- Creating a list of vectors from text chunks

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3 of 15

- Creating a list of vectors from text chunks

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Stress Testing Qdrant - Semantic Search with 90,000 Vectors - Lightning Fast Search Microservice

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  1. 1 - Stress testing quadrant
  2. 2 - Splitting text into chunks
  3. 3 - Creating a list of vectors from text chunks
  4. 4 - Creating a data folder for a machine learning model
  5. 5 - Setting up TensorFlow Hub
  6. 6 - Setting up a Python virtual environment
  7. 7 - Setting up the TensorFlow GPU environment
  8. 8 - Generating data for a machine learning model
  9. 9 - Uploading and testing the quadrant stress test
  10. 10 - Uploading a dataset to an Algolia account
  11. 11 - Trying to upload records
  12. 12 - Uploading records
  13. 13 - A look at the final numbers
  14. 14 - The power and efficiency of the search function
  15. 15 - The efficiency of the program

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