bodywork-pymc3-project
indaba-pracs-2022
| bodywork-pymc3-project | indaba-pracs-2022 | |
|---|---|---|
| 1 | 1 | |
| 13 | 172 | |
| - | 0.6% | |
| 5.3 | 0.0 | |
| almost 2 years ago | 30 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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bodywork-pymc3-project
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A tutorial on how to handle prediction uncertainty in production systems, by using Bayesian inference and probabilistic programs
All of the code is hosted in a GitHub repo, that you can use as a template for your own projects.
indaba-pracs-2022
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From Deep Learning Foundations to Stable Diffusion
This year's Deep Learning Indaba had a tutorial on diffusion models in Jax: https://github.com/deep-learning-indaba/indaba-pracs-2022/tr...
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