Vector-Based Methods for Similarity Search - TF-IDF, BM25, SBERT

The course covers three vector-based methods for similarity search: TF-IDF, BM25, and SBERT. The learning outcomes include understanding how to compare languages and identify similar documents using vector similarity search and semantic search techniques. The course aims to teach the skills of implementing TF-IDF, BM25, and Sentence-BERT algorithms. The teaching method involves a video format with a duration of 29 minutes. The intended audience for this course includes individuals interested in AI, machine learning, and building effective search engines.