What you'll learn
- Probabilistic Programming with STAN
- Bayesian Inference
- STAN
Requirements
- There is no prerequisite for the course , except some brief familiarity with the Bayesian thinking and knowledge of R
Description
In this course , the probabilistic programming for statistical inference , STAN , within Bayesian framework has been taught with many examples and mini-project styles .
During my graduate studies in applied mathematics , I did not have the resources which teach me how to write the code and how to tune it , it took me such a long journey to teach myself , this then motivated me to create these tutorials for those who want to explore the richness of the Bayesian inference .
This course , in details , explore the following models in STAN :
- Multi_variate Regression Models
- Convergence and Model Tuning
- Logistic Regression Analysis
- Quadratic Predictive Models
- Hierarchical Models
I hope this tutorial helps you to think more Bayesian and act more Bayesian.
Who this course is for:
- Anyone who is interested to know how to start a project applying Bayesian and finish it in Bayesian
Course content
- Preview03:38
- 12:45Installation of R & RStudio ( Optional)
Instructor
![Omid Rezania](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 3.7 Instructor Rating
- 16 Reviews
- 67 Students
- 4 Courses
I am graduate student in Applied Mathematics at York university , Toronto , Ontario , Canada. Previously , I had done another graduate degree in Theoretical Particle Physics which after that I joined a research team at the Montreal Neurological Institute and did research on Alzheimer`s disease and application of the AI in the diagnosis of the disorder before the initial symptoms of the dementia from the PET scans.
Currently , I do both conduct a research on the application of the AI in the early diagnosis of cancer from the scattering coefficients of the lasers from the cancerous tissues.
and also , I do teach mathematics and Physics at a college which recently I won the Canadian Meritorious Award for advising a team to win the first place at the 5th Annual Mathematical Modelling Challenge 2020.
I do like reading philosophical text books , then when I am not busy with research or teaching , I do spend my time reading books in a coffee shop.