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tutorial-course

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Detailed implementations, Jupyter tutorials and complete packages to implement and test Probabilistic Bayesian Deep Learning models. The repository contains the software implementations of the techniques discussed in the review paper "Shedding light on uncertainties in machine learning: formal derivation and optimal model selection".

  • Updated Mar 5, 2025
  • Jupyter Notebook

This repository provides a comprehensive solution and codebase for the migration from centralized to federated learning. It demonstrates centralized training, its drawbacks, and how federated learning addresses these issues. It also serves as a tutorial to guide users through the transition process.

  • Updated Oct 18, 2024
  • Jupyter Notebook

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