Search Engineering Tutorials
Master vector search modalities, reranking, and retrieval quality.
| Tutorial | Objective | Stack | Time | Level |
|---|---|---|---|---|
| Relevance Feedback | Relevance Feedback Retrieval in Qdrant | Python | 30m | Intermediate |
| Collaborative Filtering | Collaborative filtering using sparse embeddings. | Python | 45m | Intermediate |
| Multivector Document Retrieval | PDF RAG using ColPali and embedding pooling. | Python | 30m | Intermediate |
| Measuring ANN Recall | Measure ANN recall with the Web UI and tune HNSW parameters. | Web UI | 15m | Beginner |
| Multivectors and Late Interaction | Effective use of multivector representations. | Python | 30m | Intermediate |
| Multi-Representation Search | Fuse title, summary, chunk, and tag vectors with named vectors and the Query API. | Python | 45m | Intermediate |
| Static Embeddings | Evaluate the utility of static embeddings. | Python | 20m | Intermediate |
| Branch-Aware Search | Scope search to a branch’s live view in a versioned corpus, inherited from its ancestors. | Python | 25m | Intermediate |
