Explores document retrieval, classification, sentiment analysis, TF-IDF matrices, nearest-neighbor methods, matrix factorization, regularization, LDA, contextualized word vectors, and BERT.
Introduces the basics of information retrieval, covering document representation, query expansion, and TF-IDF for document ranking.
Covers the basics of linear algebra, including matrix operations and singular value decomposition.
Explores Singular Value Decomposition and its role in unsupervised learning and dimensionality reduction, emphasizing its properties and applications.
