Vyacheslav EfimovinTowards Data ScienceSimilarity Search, Part 7: LSH CompositionsDive into combinations of LSH functions to guarantee a more reliable searchJul 24, 2023Jul 24, 2023
Vyacheslav EfimovinTowards Data ScienceSimilarity Search, Part 6: Random Projections with LSH ForestUnderstand how to hash data and reflect its similarity by constructing random hyperplanesJul 21, 20231Jul 21, 20231
Vyacheslav EfimovinTowards Data ScienceSimilarity Search, Part 5: Locality Sensitive Hashing (LSH)Explore how similarity information can be incorporated into hash functionJun 24, 20231Jun 24, 20231
Vyacheslav EfimovinTowards Data ScienceSimilarity Search, Part 4: Hierarchical Navigable Small World (HNSW)Hierarchical Navigable Small World (HNSW) is a state-of-the-art algorithm used for an approximate search of nearest neighbours. Under the…Jun 16, 20237Jun 16, 20237
Vyacheslav EfimovinTowards Data ScienceSimilarity Search, Part 3: Blending Inverted File Index and Product QuantizationIn the first two parts of this series we have discussed two fundamental algorithms in information retrieval: inverted file index and…May 19, 20231May 19, 20231
Vyacheslav EfimovinTowards Data ScienceSimilarity Search, Part 2: Product QuantizationLearn a powerful technique to effectively compress large dataMay 10, 20233May 10, 20233
Vyacheslav EfimovinTowards Data ScienceSimilarity Search, Part 1: kNN & Inverted File IndexSimilarity search is a popular problem where given a query Q we need to find the most similar documents to it among all the documents D.Apr 28, 20232Apr 28, 20232