The different types of model selection techniques in machine learning are -
Resampling Techniques - Uses random sampling to generate multiple subsets of a given data set, which can be used to train and evaluate multiple models.
Probabilistic Techniques - Used for selecting the finest model from a set of models by estimating the probability distributions of each model, given the data.