Probabilistic Information Retrieval

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Related lectures (30)

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Estimation and Confidence Intervals

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Maximum Likelihood Estimation

Covers maximum likelihood estimation to estimate parameters by maximizing prediction accuracy, demonstrating through a simple example and discussing validity through hypothesis testing.

Logistic Regression: Probability Modeling

Covers logistic regression for binary classification using probability modeling and optimization methods.

Estimation Methods in Probability and Statistics

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Probabilistic Retrieval: Practical Relevance Feedback

Explores practical relevance feedback in probabilistic retrieval and query optimization.

An Introduction to Systems Engineering: Requirements, Architecture, and Concept Generation

Covers the 'V-Model' of Systems Engineering, emphasizing good requirements, system architecture, concept generation, and concept selection.

Statistical Hypothesis Testing

Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.

Probability and Statistics

Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.

Bayesian Inference: Estimation & Demystification

Covers the concepts of Demystification, Estimation, and Bayesian Inference in the context of Bayesian statistics.

Probability and Estimation in Statistics

Introduces probability, estimation methods, linear models, testing, and advanced regression techniques.