Information Retrieval BasicsIntroduces the basics of information retrieval, covering document representation, query expansion, and TF-IDF for document ranking.
Handling Text: Document Retrieval, Classification, Sentiment AnalysisExplores document retrieval, classification, sentiment analysis, TF-IDF matrices, nearest-neighbor methods, matrix factorization, regularization, LDA, contextualized word vectors, and BERT.
Probabilistic RetrievalCovers Probabilistic Information Retrieval, modeling relevance as a probability, query expansion, and automatic thesaurus generation.
Latent Semantic IndexingCovers Latent Semantic Indexing, word embeddings, and the skipgram model with negative sampling.
Information retrieval: vector spaceCovers the basics of information retrieval using vector space models and practical exercises on relevance feedback and posting list scanning.
