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3 Traditional Methods for Similarity Search (Jaccard, w-shingling, Levenshtein)
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Classroom Contents
Vector Similarity Search and Faiss Course
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- 1 3 Traditional Methods for Similarity Search (Jaccard, w-shingling, Levenshtein)
- 2 3 Vector-based Methods for Similarity Search (TF-IDF, BM25, SBERT)
- 3 Faiss - Introduction to Similarity Search
- 4 Choosing Indexes for Similarity Search (Faiss in Python)
- 5 Locality Sensitive Hashing (LSH) for Search with Shingling + MinHashing (Python)
- 6 How LSH Random Projection works in search (+Python)
- 7 IndexLSH for Fast Similarity Search in Faiss
- 8 Product Quantization for Vector Similarity Search (+ Python)
- 9 Faiss - Vector Compression with PQ and IVFPQ (in Python)
- 10 HNSW for Vector Search Explained and Implemented with Faiss (Python)
- 11 Evaluation Measures for Search and Recommender Systems
- 12 Metadata Filtering for Vector Search + Latest Filter Tech
- 13 Composite Indexes and the Faiss Index Factory
- 14 Best Indexes for Similarity Search in Faiss
