ShuaiGuo16/Gaussian-Process
Implementing a Gaussian Process regression model from scratch
This project helps data scientists and machine learning engineers understand the inner workings of Gaussian Process regression. It takes in sample data points and outputs a predictive model with uncertainty estimates, allowing for robust statistical analysis and forecasting. This is for individuals who build and apply predictive models.
No commits in the last 6 months.
Use this if you are a data scientist or machine learning engineer who wants to deeply understand and implement a Gaussian Process regression model from its fundamental components.
Not ideal if you are looking for a high-level library to apply Gaussian Processes without needing to understand the underlying mathematical implementation.
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Last pushed
Feb 04, 2021
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