This project is a computational statistics textbook and Bayesian data analysis course. It serves as a guide for performing statistical inference and quantifying uncertainty through a probabilistic programming workflow using Python. The resource employs a computation-first pedagogy, teaching Bayesian methods and parameter estimation through executable code and simulations instead of formal mathematical notation. It provides a practical approach to implementing Markov Chain Monte Carlo sampling to estimate posterior distributions. The content covers building probabilistic models, integrating e
Code for Machine Learning with TensorFlow: 2nd Edition Published by Manning Publications
RxJava Essentials 中文翻译版 仅供交流学习使用，严禁商业用途
The main features of yuxingxin/rxjava-essentials-cn are: Educational Books.
Open-source alternatives to yuxingxin/rxjava-essentials-cn include: camdavidsonpilon/probabilistic-programming-and-bayesian-methods-for-hackers — This project is a computational statistics textbook and Bayesian data analysis course. It serves as a guide for… chrismattmann/mlwithtensorflow2ed — Code for Machine Learning with TensorFlow: 2nd Edition Published by Manning Publications.