Python-Socket-Practice/bayesian-useful-links.txt at office-websocket · chenweichen/Python-Socket-Practice · GitHub

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# Bayesian useful links

## No.:
## Title:
## https links:

1.
Bayesian models of perception and action - Wei Ji Ma, Konrad Kording, and Daniel Goldreich, with original artwork by Brennan Klein
https://www.cns.nyu.edu/malab/bayesianbook.html

https://www.cns.nyu.edu/malab/static/files/Bayesian_models_of_perception_and_action_v3.pdf

https://www.cns.nyu.edu/malab/static/files/Bayesian_models_of_perception_and_action_v2.pdf


2.
Mattias Villani - Bayesian Beyond Belief
https://www.mattiasvillani.com

https://github.com/mattiasvillani


3.
Home for the course Machine Learning,
7.5 credits given every spring semester at the Department of Statistics at Stockholm University.
https://github.com/mattiasvillani/MLcourse

Machine Learning - a first course for engineers and scientists (MLES) by Lindholm et al. (2021).
Forthcoming at Cambridge University Press. A free PDF version is available here.

http://smlbook.org/book/sml-book-draft-latest.pdf

The previous title of the book was 'Supervised Machine Learning'.


4.
Bayesian Learning course at Stockholm University
https://github.com/mattiasvillani/BayesLearnCourse

The course gives a solid introduction to Bayesian statistical inference,
with special emphasis on models and methods in computational statistics and machine learning.


5.
Course material for the PhD course in Advanced Bayesian Learning
https://github.com/mattiasvillani/AdvBayesLearnCourse


6.
Home for the book-in-progress 'Bayesian Learning'
https://github.com/mattiasvillani/BayesianLearningBook