PGM-Lab/probai-2021-pyro
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
This provides materials for learning how to build and understand probabilistic models using a tool called Pyro. You'll work through interactive notebooks, starting with basic probabilistic concepts and moving to more complex techniques like Bayesian regression and variational autoencoders. This resource is for data scientists, machine learning engineers, and researchers interested in applying probabilistic programming to their work.
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Use this if you want to learn the fundamentals of probabilistic programming and variational inference, with practical examples using the Pyro library.
Not ideal if you are looking for a plug-and-play solution for a specific data analysis task without needing to understand the underlying statistical models.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Nov 09, 2021
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