When and how to use weigthed regression.
An example on over optimistic inference.
A few comments to have in mind about R2
Some details about OLS as smoothing of the training data. Weighted average of Y by distance of X to the center and variance of X.
Some details about Bias Variance Tradeoff
Softmax vs Sigmoid. How weights are updated in the last layer.
Xgboost to quickly model winning probabilities with monotonic constraints.