Completed
Locality Sensitive Hashing (LSH) for Search with Shingling + MinHashing (Python)
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Vector Similarity Search and Faiss Course
Automatically move to the next video in the Classroom when playback concludes
- 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
