Introduces the basics of information retrieval, covering document representation, query expansion, and TF-IDF for document ranking.
Introduces the basics of information retrieval, covering text-based and Boolean retrieval, vector space retrieval, and similarity computation.
Covers Latent Semantic Indexing, a method to improve information retrieval by mapping documents and queries into a lower-dimensional concept space.
Explores document retrieval, classification, sentiment analysis, TF-IDF matrices, nearest-neighbor methods, matrix factorization, regularization, LDA, contextualized word vectors, and BERT.
Covers Probabilistic Information Retrieval, modeling relevance as a probability, query expansion, and automatic thesaurus generation.
