Temas relacionados
Este curso incluye
- 17 h 49 min de vídeo
- 29 lecciones
- Nivel: Intermedio
- Idioma: English
- Recordamos dónde lo dejaste
- Gratis por completo, sin tarjeta
Lecciones
3 secciones · 29 lecciones · 17 h 49 min duración total
Lecciones 1 a 1010 lecciones · 6 h 29 min
- BDA course 1.1 Introduction to uncertainty and modelling18 min
- BDA course 1.2 Introduction to the course contents9 min
- BDA 2019 Lecture 2.1 Bayesian inference, observation model, likelihood, posterior, and binomial37 min
- BDA 2019 Lecture 2.2 priors and prior information, and one parameter normal model44 min
- BDA course 2 extra: likelihood, normalization, density, model M14 min
- BDA 2019 Lecture 3 on multiparameter models. joint, marginal and conditional distribution, normal1 h 26 min
- BDA 2019 Lecture 4.1 numerical issues, Monte Carlo, how many simulation draws are needed, ...50 min
- BDA 2019 Lecture 4.2 direct simulation, curse of dimensionality, rejection and importance sampling43 min
- BDA 2019 Lecture 5.1 Markov chain Monte Carlo, Gibbs sampling, and Metropolis algorithm51 min
- BDA 2019 Lecture 5.2 warm up, convergence diagnostics, R-hat, and effective sample size38 min
Lecciones 11 a 2010 lecciones · 6 h 36 min
- BDA 2019 Lecture 6.1 HMC, NUTS, dynamic HMC, and HMC specific convergence diagnostics50 min
- BDA 2019 Lecture 6.2 probabilistic programming and Stan46 min
- Stan and probabilistic programming introduction39 min
- BDA 2019 Lecture 7.1 hierarchical models44 min
- BDA 2019 Lecture 7.2 exchangeability16 min
- BDA 2019 Lecture 8.1 model checking47 min
- BDA 2019 Lecture 8.2 cross-validation part 146 min
- BDA 2019 Lecture 9.1 PSIS-LOO and K-fold cross-validation51 min
- BDA 2019 Lecture 9.2 model comparison and selection30 min
- BDA 2019 Lecture 9.3 extra lecture on projection predictive variable selection26 min
Lecciones 21 a 299 lecciones · 4 h 45 min
- BDA 2019 Lecture 10.1 Decision analysis51 min
- BDA 2019 Lecture 11.1 Normal approximation, Laplace approximation.44 min
- BDA 2019 Lecture 11.2 Large sample theory and counter examples43 min
- BDA 2019 Lecture 12.1 Frequency evaluation, hypothesis testing, and variable selection55 min
- BDA 2019 Lecture 12.2 Summary of modeling data collection, linear models, Lasso, and Gaussian proces48 min
- BDA course 2.1 Observation model, likelihood, posterior, and binomial model15 min
- BDA course 2.2 Predictive distribution and benefit of integration8 min
- BDA course 2.3 Priors and prior information20 min
Private videoEl canal ha borrado u ocultado este vídeo.
Qué necesitas
- Ayuda tener base: el curso sigue a partir de lo básico.
Descripción
Bayesian Data Analysis course videos https://avehtari.github.io/BDA_course_Aalto/
Para quién es este curso
- Quien ya conoce lo básico de Datos y AI.
Esos dos puntos son nuestra lectura del nivel. La descripción es del autor.