|
You are here |
jduncstats.com | ||
| | | | |
tiao.io
|
|
| | | | | One weird trick to make exact inference in Bayesian logistic regression tractable. | |
| | | | |
emiruz.com
|
|
| | | | | ||
| | | | |
twiecki.io
|
|
| | | | | [AI summary] This blog post discusses hierarchical linear regression in PyMC3, highlighting its advantages over non-hierarchical Bayesian modeling. The author explores how hierarchical models can effectively handle multi-level data by leveraging the 'shrinkage-effect', which improves predictions by borrowing strength from related groups. Using the radon dataset, the post compares individual and hierarchical models, demonstrating that the hierarchical approach provides more accurate and robust estimates, especially in cases with limited data. The key takeaway is that hierarchical models balance individual and group-level insights, offering the best of both worlds in data analysis. | |
| | | | |
comsci.blog
|
|
| | | In this blog post, we will learn about vision transformers (ViT), and implement an MNIST classifier with it. We will go step-by-step and understand every part of the vision transformers clearly, and you will see the motivations of the authors of the original paper in some of the parts of the architecture. | ||