Tutorials for Vector Search and HFE #85
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dwdougherty
previously approved these changes
Jul 22, 2025
Co-authored-by: David Dougherty <[email protected]>
dwdougherty
previously approved these changes
Jul 29, 2025
Co-authored-by: David Dougherty <[email protected]>
dwdougherty
approved these changes
Jul 31, 2025
| @@ -7,7 +7,7 @@ Redis Stack offers an enhanced Redis experience via the following Redis Query En | |||
| - Geospatial queries | |||
| - Aggregations | |||
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| The Redis Query Engine features of Redis Stack allow you to use Redis as a: | |||
| The Redis Query Engine features you to use Redis as a: | |||
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| The Redis Query Engine features you to use Redis as a: | |
| The Redis Query Engine features allow you to use Redis as a: |
| ### Store movie documents with vector embeddings | ||
| Semantic search uses vector embeddings — numeric representations of text that capture meaning, enabling search by intent rather than keywords. | ||
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| We'll import a dataset of plot summaries, each paired with an embedding vector. |
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| We'll import a dataset of plot summaries, each paired with an embedding vector. | |
| You'll import a dataset of plot summaries, each paired with an embedding vector. |
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