gp-python
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kernel understanding
Hi,starting with apology because this is not an issue.I am asking for your help to understand kernel. I've started my undergrad final year project and my supervisor told me that it would be something like predicting just as the example given in scikit learn doc- gaussian process(https://scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_co2.html) .But I am not understanding the kernel.Why we use kernel and how can I know which kernel to use when or what is the function of each kernel?Do all they smooth the curve?When should one combine kernel? Actually I previously have zero knowledge on this but I am willing to learn from any source that would help me to proceed this research.Can you share any link or do you have any suggestion which will help me gather the insights of kernel.Actually,I want to understand the meaning of every line of the above mentioned link and in which kernel plays an important role i think.