plugyawn/gp-zoo
A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably including Stochastic Variational Gaussian Processes.
This project provides pre-built code for advanced statistical modeling, specifically Gaussian Process regression. It takes your raw data, like time-series measurements or experimental results, and outputs predictions and classifications, helping you understand trends or categorize outcomes. It's designed for data scientists and researchers who work with complex datasets and need robust, interpretable predictions.
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Use this if you are a data scientist or researcher working with complex datasets and need to implement advanced Gaussian Process models for regression or classification tasks.
Not ideal if you are looking for a simple, out-of-the-box machine learning tool without needing to dive into the underlying model implementations.
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Last pushed
Nov 19, 2022
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