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Probabilistic Information Retrieval
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Related lectures (37)
Probability and Statistics
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Explores joint random variables, conditional density, and independence in probability and statistics.
Statistics: Exploratory Data Analysis
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Probability and Statistics
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Probability and Statistics: Basics and Applications
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Elements of Statistics: Probability and Random Variables
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Normal Distribution: Properties and Calculations
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Covers the normal distribution, including its properties and calculations.
Estimating Expectation
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Explores the estimation of expectation for discrete random variables, emphasizing its importance in probability theory.
Elements of Statistics
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Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.
Gaussian Naive Bayes & K-NN
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Graph Coloring and Directed Cycles
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Pre-Training: BiLSTM and Transformer
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Delves into pre-training BiLSTM and Transformer models for NLP tasks, showcasing their effectiveness and applications.
Statistical Theory: Cramér-Rao Bound & Hypothesis Testing
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Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.
Discrete-Time Markov Chains: Definitions
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Optimal Betting Strategy
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Heat Transfer: Equilibrium Approach and Thermodynamic Potentials
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Linear Regression Basics
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Information retrieval: vector space
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Covers the basics of information retrieval using vector space models and practical exercises on relevance feedback and posting list scanning.
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