User Guide¶
For a quick start, take a look at the Examples.
The user guide contains more detailed information about using ProbFlow, including:
A brief description of Bayesian modeling,
Using Distributions, Parameters, and Modules to create Bayesian Models,
How to fit those models to data,
How to make predictions with those models,
How to evaluate the performance of a model,
How to inspect a model’s structure and the values of its parameters,
How to use ProbFlow’s Ready-made Models,
How to perform actions mid-training with Callbacks,
How to load data on-the-fly with Data Generators,
How to save and load models,
How to choose your backend and default datatype, and
Mathematical Details about how ProbFlow fits Bayesian models.