training gradient boosting algorithm in python testing in Golang What are the best strategy to train and save a gradient boosting algorithm, e.g. LightGBM or XGboost or Catboost in Python but load the model in GoLang and make prediction with Golang ?
There's actually a few libraries that handle the inference part well.  https://github.com/dmitryikh/leaves is probably the most common one and seems to fit your need.