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Related lectures (32)

Vector Space Retrieval Exercise

Covers TF-IDF computation, document vectors, cosine similarity, and precision formulas.

Document Retrieval and Classification

Covers document retrieval, classification, sentiment analysis, and topic detection using TF-IDF matrices and contextualized word vectors like BERT.

Introduction to Information Retrieval

Introduces the basics of information retrieval, covering text-based retrieval, document features, similarity functions, and the difference between Boolean and ranked retrieval.

Information Retrieval: Fagin's Algorithm

Covers the implementation of Fagin's algorithm for information retrieval, focusing on efficient document retrieval.

Embedding Models: Concepts and Retrieval

Covers embedding models for document retrieval, latent semantic indexing, SVD, and topic models.

Text Data Processing: Basics & Techniques

Introduces the basics of text data processing, covering document retrieval, classification, sentiment analysis, and topic detection.

Text Data Analysis: Techniques and Applications

Explores handling text data, deriving clean datasets from unstructured text, and various text analysis techniques.

Handling Text: Document Retrieval, Classification, Sentiment Analysis

Explores document retrieval, classification, sentiment analysis, TF-IDF matrices, nearest-neighbor methods, matrix factorization, regularization, LDA, contextualized word vectors, and BERT.

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Distributed Information Systems: Overview and Models

Covers Distributed Information Systems, key tasks, methods, projects, evaluation, and exam support.

Numerical Methods: Euler and Crank-Nicolson

Covers Euler and Crank-Nicolson methods for solving differential equations.

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