Tutorials
These tutorials demonstrate different ways you can build vector search into your applications.
| Essential How-Tos | Description | Stack |
|---|---|---|
| Semantic Search for Beginners | Create a simple search engine locally in minutes. | Qdrant |
| Simple Neural Search | Build and deploy a neural search that browses startup data. | Qdrant, BERT, FastAPI |
| Neural Search with FastEmbed | Build and deploy a neural search with our FastEmbed library. | Qdrant |
| Bulk Upload Vectors | Upload a large scale dataset. | Qdrant |
| Asynchronous API | Communicate with Qdrant server asynchronously with Python SDK. | Qdrant, Python |
| Create Dataset Snapshots | Turn a dataset into a snapshot by exporting it from a collection. | Qdrant |
| Load HuggingFace Dataset | Load a Hugging Face dataset to Qdrant | Qdrant, Python, datasets |
| Measure Retrieval Quality | Measure and fine-tune the retrieval quality | Qdrant, Python, datasets |
| Search Through Code | Implement semantic search application for code search tasks | Qdrant, Python, sentence-transformers, Jina |
| Setup Collaborative Filtering | Implement a collaborative filtering system for recommendation engines | Qdrant |