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Related lectures (30)

Page 3 of 3

Variational Inference and Neural Networks

Covers variational inference and neural networks for classification tasks.

Probability Theory: Midterm Solutions

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.

Bayesian Inference: Beta-Bernoulli Model

Explores the Beta distribution, Bayesian inference, and posterior calculation in the Beta-Bernoulli model.

Confidence Intervals and Hypothesis Testing

Explores confidence intervals, hypothesis testing, and ROC curves in statistical analysis.

Stochastic Models for Communications

Explores stochastic models for communications, covering mean, variance, characteristic functions, inequalities, various discrete and continuous random variables, and properties of different distributions.

Probabilistic Topic Models: Latent Dirichlet Allocation

Explores Latent Dirichlet Allocation, a probabilistic topic model for document clustering and analysis using distributions over words and topics.

Lexicons, n-grams and Language Models

Explores lexicons, n-grams, and language models, emphasizing their importance in recognizing words and the effectiveness of n-grams for various tasks.

Nonuniform Random Number Distributions: Examples and Methods

Explores nonuniform random number distributions, examples, methods, and generation techniques.

Generalised Linear Models: Regression with Exponential Family Responses

Covers regression with exponential family responses using Generalised Linear Models.

Probability Distributions: Basics and Properties

Covers the basics of probability distributions, including mean, variance, and properties of random variables.