System and method for multi-task learning

A non-transitory computer readable medium comprising one or more sequences of instructions, which, when executed by one or more processors, causes a computing system to perform operations comprising:

• identifying, by the computing system, information related to a sporting event, the information comprising dense features of the sporting event and sparse features of the sporting event;
• generating, by the computing system, dense representations of the sparse features using one or more embedding layers of a machine learning architecture;
• generating, by the computing system, an input vector comprising the dense features and the dense representations of the sparse features;
• simultaneously generating, by the computing system using a mixture density layer of the machine learning architecture, a plurality of values associated with a next event to occur based on the input vector;
• and
• outputting, by the computing system, a graphical user interface comprising graphical representations of the plurality of values.

A system, comprising:

• a processor;
• and
• a memory having programming instructions stored thereon, which, when executed by the processor, causes the system to perform operations comprising:
• identifying information related to a sporting event, the information comprising dense features of the sporting event and sparse features of the sporting event;
• generating dense representations of the sparse features using one or more embedding layers of a machine learning architecture;
• generating an input vector comprising the dense features and the dense representations of the sparse features;
• simultaneously generating, using a mixture density layer of the machine learning architecture, a plurality of values associated with a next event to occur based on the input vector;
• and
• outputting a graphical user interface comprising graphical representations of the plurality of values.