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Copy file name to clipboardExpand all lines: qdrant-landing/content/course/essentials/day-1/chunking-strategies.md
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@@ -54,7 +54,7 @@ This is where chunking comes in. The goal is to have chunks
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By breaking a document into focused chunks, each chunk gets its own vector that accurately represents a specific idea. This allows the search to be far more precise.
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**Example:** Consider a multi-page Document like the [Qdrant Collection Configuration Guide of day 7](/course/essentials/day-7/collection-configuration-guide/) covering everything from HNSW to sharding and quantization.
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**Example:** Consider a multi-page Document like the [Qdrant Collection Configuration Guide of Day 7](/course/essentials/day-7/collection-configuration-guide/) covering everything from HNSW to sharding and quantization.
Copy file name to clipboardExpand all lines: qdrant-landing/content/course/essentials/day-1/movie-search-system.md
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## Step 6: Advanced Features
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Note: If you are already familiar Qdrant's filterable HNSW, you will know that effective filtering and grouping often relies on creating a [payload index](/documentation/concepts/indexing/#payload-index) before building HNSW indexes. To keep things simple in this tutorial, we will do a basic search with filters without payload indexes and talk about proper usage of payload indexes on [day 2](/content/course/essentials/day-2/_index.md) of this course.
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Note: If you are already familiar Qdrant's filterable HNSW, you will know that effective filtering and grouping often relies on creating a [payload index](/documentation/concepts/indexing/#payload-index) before building HNSW indexes. To keep things simple in this tutorial, we will do a basic search with filters without payload indexes and talk about proper usage of payload indexes on [Day 2](/content/course/essentials/day-2/_index.md) of this course.
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