Virtual rendering of machine learning models

A method for visual manipulation and execution of machine learning models rendered in a three-dimensional space, the method comprising:

• receiving configuration data comprising one or more components representing a machine learning model, wherein each component of the one or more components comprises a plurality of nodes, one or more edges, and associated weight matrices of the machine learning model;
• generating a three-dimensional representation of the machine learning model by (1) generating virtual objects corresponding to the plurality of nodes and the one or more edges and (2) configuring values of virtual object parameters for the virtual objects based on the associated weight matrices;
• detecting a user gesture that indicates a command to perform a modification of the machine learning model;
• responsive to detecting the user gesture, causing execution of a modified machine learning model using input data and obtaining output data for one or more modified components associated with the modified machine learning model;
• and
• generating, for display, a new three-dimensional representation of the modified machine learning model by (1) modifying the values of the virtual object parameters based on the one or more modified components and (2) configuring the values of the virtual object parameters based on the associated weight matrices of the one or more modified components.

One or more non-transitory, computer-readable media comprising instructions recorded thereon that, when executed by one or more processors, cause operations for visual manipulation and execution of machine learning models rendered in a three-dimensional space, comprising:

• accessing configuration data comprising one or more data structures representing a machine learning model, wherein a data structure of the one or more data structures corresponds to a layer of the machine learning model and comprises one or more nodes, edges, and associated weight matrices;
• generating a three-dimensional representation of the machine learning model by (1) generating virtual objects corresponding to the one or more nodes and edges and (2) configuring values of virtual object parameters for the virtual objects based on the associated weight matrices;
• detecting a user gesture that causes a modification of the machine learning model;
• responsive to detecting the user gesture, causing execution of a modified machine learning model using input data and obtaining data for one or more modified data structures associated with the modified machine learning model;
• and
• generating, for display, a new three-dimensional representation of the machine learning model by configuring the values of the virtual object parameters based on the associated weight matrices of the one or more modified data structures.