What is Gaussian process in a nutshell?
I'm trying to understand the concept of Gaussian process in a simplified and straightforward way. Could someone please explain it to me in a nutshell, highlighting its key characteristics and applications?
Why do we need Gaussian process?
We need Gaussian processes because they provide a flexible and powerful framework for non-parametric regression and classification. By modeling distributions over functions, Gaussian processes can capture complex patterns and uncertainties in data, making them suitable for a wide range of machine learning tasks.
Where is Gaussian process used?
I'm wondering about the applications of Gaussian process. Could you tell me where it's commonly used?
What are the drawbacks of the Gaussian process?
I'm exploring the limitations of Gaussian processes and would like to understand the potential drawbacks or challenges associated with using them. Specifically, I'm interested in computational complexity, interpretability, and any other known issues.