This video will walk you through the concept of Bayesian curve fitting. It will use an example of sine function as a ground truth. It will also demonstrate the impact of regularization and how the fitting gets better if lambda (regularization parameter) is selected between 0-1.
Github link for the code is https://github.com/ruchikaverma-iitg/...
Link for the ML lectures and codes
• V7 Bayesian Curve Fitting | Maximum Likeli...
https://github.com/ruchikaverma-iitg/...
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