blei-lab/edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
This library helps machine learning researchers and data scientists build and experiment with probabilistic models, from simple hierarchical structures to complex deep generative models. It takes in your raw data and a probabilistic model definition, then helps you analyze the underlying patterns, make predictions, and assess model quality. This is for users who develop and refine advanced statistical or machine learning algorithms.
4,843 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or data scientist looking to rapidly prototype, train, and evaluate a wide range of probabilistic models, especially those integrating deep learning architectures.
Not ideal if you are looking for a pre-built, off-the-shelf solution for common data analysis tasks without needing to design custom probabilistic models or delve into their inference mechanisms.
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Last pushed
Mar 18, 2024
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