kyle-dorman/bayesian-neural-network-blogpost
A Jupyter notebook tutorial explaining how to build a Bayesian deep learning classifier with uncertainty estimation using Keras.
Not currently ranked — collecting fresh signals.
star history
This repository contains a Jupyter notebook implementing a Bayesian deep learning classifier with uncertainty estimation. It covers Bayesian methods for deep learning including techniques for modeling both aleatoric (data) and epistemic (model) uncertainty. The implementation uses Keras as the deep learning framework and includes CIFAR-10 image classification examples.
Frequently asked
- What is kyle-dorman/bayesian-neural-network-blogpost?
- A Jupyter notebook tutorial explaining how to build a Bayesian deep learning classifier with uncertainty estimation using Keras.
- Is bayesian-neural-network-blogpost open source?
- Yes — kyle-dorman/bayesian-neural-network-blogpost is an open-source project tracked on heatdrop.
- What language is bayesian-neural-network-blogpost written in?
- kyle-dorman/bayesian-neural-network-blogpost is primarily written in Jupyter Notebook.
- How popular is bayesian-neural-network-blogpost?
- kyle-dorman/bayesian-neural-network-blogpost has 492 stars on GitHub.
- Where can I find bayesian-neural-network-blogpost?
- kyle-dorman/bayesian-neural-network-blogpost is on GitHub at https://github.com/kyle-dorman/bayesian-neural-network-blogpost.