Embedding Models: Concepts and Retrieval

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Singular Value Decomposition: Applications and Interpretation

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

SVD: Singular Value Decomposition

Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.

Information Retrieval Basics

Introduces the basics of information retrieval, covering document representation, query expansion, and TF-IDF for document ranking.

Linear Algebra Review

Covers the basics of linear algebra, including matrix operations and singular value decomposition.

Information Extraction: Algorithms and Techniques

Explores algorithms and techniques for information extraction, including Viterbi algorithm, named entities recognition, and distant supervision.

Unsupervised Learning: Principal Component Analysis

Covers unsupervised learning with a focus on Principal Component Analysis and the Singular Value Decomposition.

Latent semantic indexing: inverted files

Explores term-offset indices in inverted files and relevance feedback solutions.

Singular Value Decomposition

Covers the Singular Value Decomposition theorem and its application in decomposing matrices.

Unsupervised Learning: Movie Recommendation

Covers unsupervised learning for movie recommendation using singular value decomposition.

Information Extraction: Methods and Applications

Explores methods for information extraction, including traditional and embedding-based approaches, supervised learning, distant supervision, and taxonomy induction.