Information Retrieval BasicsIntroduces the basics of information retrieval, covering text-based and Boolean retrieval, vector space retrieval, and similarity computation.
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.
Information retrieval: vector spaceCovers the basics of information retrieval using vector space models and practical exercises on relevance feedback and posting list scanning.
Latent Semantic IndexingCovers Latent Semantic Indexing, word embeddings, and the skipgram model with negative sampling.
