Systems and methods of multimodal clustering using machine learning

A method, comprising:

• generating, by a first model trained using machine learning with input including one or more first features each associated with data structures having a plurality of distinct data types, one or more second features compatible with one of the distinct data types;
• generating, by a second model trained with input including the second features, a plurality of cluster classifications each compatible with one or more of the distinct data types;
• and
• causing a user interface to present one or more of the data structures rendered according to a spatial structure based on the second features and the cluster classifications.

A computer readable medium including one or more instructions stored thereon and executable by a processor to:

• generate, by the processor via a first model trained using machine learning with input including one or more first features each associated with data structures having a plurality of distinct data types, one or more second features compatible with one of the distinct data types;
• generate, by the processor via a second model trained with input including the second features, a plurality of cluster classifications each compatible with one or more of the distinct data types;
• and
• cause, the processor, a user interface to present one or more of the data structures rendered according to a spatial structure based on the second features and the cluster classifications.