Natural Language Generation: Decoding & Training

Related lectures (26)

Page 2 of 3

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Covers the concept of property testing using statistical methods.

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Introduces multivariate statistics, covering normal distribution properties and characteristic functions.

Introduces the concept of a Markov process and chain in configuration sampling.

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Covers generative models with a focus on self-attention and transformers, discussing sampling methods and empirical means.

Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.

Explores air pollution analysis using wind data, probability distributions, and trajectory models for air quality assessment.