Item type discovery and classification using machine learning

Systems and methods are provided for learning item types of items listed in an electronic repository, and for training a machine learning model to predict the item type of a given input item. For example, a machine learning model may be obtained or accessed that has been previously trained to classify an input item to a browse node. Vector representations of individual items assigned to different browse nodes may be obtained from an intermediate layer of the previously trained machine learning model, and a vector representation of individual browse nodes may then be generated based on the vector representations of individual items assigned to that browse node. A clustering algorithm may be applied to the browse node vector representations in order to identify clusters of similar browse nodes, where individual clusters may represent different unique item types.