Scikitlearn offers a great documentation with really good minimum examples. Check these two out:
- Support Vector Regression (SVR) using linear and non-linear kernels — scikit-learn 1.2.2 documentation
- Prediction Intervals for Gradient Boosting Regression — scikit-learn 1.2.2 documentation
There are many great other supervised learning models available on scikitlearn which you can explore here: 1. Supervised learning — scikit-learn 1.2.2 documentation
In addition if you have a very specific domain function for your regression model in mind you want to fit: Here you can also find a repo where I tried to solve some nonlinear differential equations utilizing probabilistic models and estimate model parameters w/ scipi and Tensorflow (and also Julia for neural ODEs):
Hope that helps!
Best regards
Christian