Machine learning-based temporal startup predictive system

A system comprising:

• one or more hardware processors;
• and
• a memory storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
• determining a training dataset of features associated with different funding, exit, and closure events and corresponding times of the funding, exit, and closure events from historical financial data;
• training a temporal prediction model using the training dataset, the temporal prediction model comprising a recurrent neural network,
• during runtime, accessing new data associated with potential future investment opportunities with startups;
• determining company features based, in part, on the new data;
• applying the company features to the temporal prediction model to simultaneously predict a next event and a time of the next event for each startup;
• and
• causing presentation of a user interface that presents the predicted next event and the predicted time of the predicted next event for each startup.

A machine-storage medium comprising instructions which, when executed by one or more hardware processors of a machine, cause the machine to perform operations comprising:

• determining a training dataset of features associated with different funding, exit, and closure events and corresponding times of the funding, exit, and closure events from historical financial data;
• training a temporal prediction model using the training dataset, the temporal prediction model comprising a recurrent neural network;
• during runtime, accessing new data associated with potential future investment opportunities with startups;
• determining company features based, in part, on the new data;
• applying the company features to the temporal prediction model to simultaneously predict a next event and a time of the next event for each startup;
• and
• causing presentation of a user interface that presents the predicted next event and the predicted time of the predicted next event for each startup.