System and method for serverless modification and execution of machine learning algorithms

A system comprising:

• one or more processors, coupled with memory, to:
• format event data from at least one network source;
• generate a computing instance by inputting the formatted event data into a serverless computing system, the computing instance configured to cause the serverless computing system to apply at least one machine learning algorithm of a plurality of machine learning algorithms to the formatted event data;
• select the at least one machine learning algorithm from the plurality of machine learning algorithms from a data repository, the at least one machine learning algorithm selected based on a type or format of the event data;
• insert additional data associated with the event data into the computing instance, wherein insertion of the additional data causes the one or more processors to generate a modified computing instance associated with the event data, the modified computing instance configured to cause the serverless computing system to generate a modified machine learning algorithm by modifying execution of the at least one machine learning algorithm based on the additional data;
• perform, at runtime, at least one of (i) compressing the modified machine learning algorithm responsive to determining the modified machine learning algorithm exceeds a memory or computing resource restriction of the modified computing instance, or (ii) maintaining the modified machine learning algorithm responsive to determining the serverless computing system comprises a feature to automatically scale memory or computing resources;
• transmit a request to cause the serverless computing system to execute the modified computing instance using the modified machine learning algorithm;
• receive outlier data associated with the event data based on execution of the modified computing instance;
• and
• transmit, to a client device, data to cause the client device to display a graphical presentation of the outlier data.

A non-transitory computer readable medium (CRM) having one or more instructions stored thereon, the one or more instructions executable by one or more processors to:

• format event data from at least one network source;
• generate a computing instance by inputting the formatted event data into a serverless computing system, the computing instance configured to cause the serverless computing system to apply at least one machine learning algorithm of a plurality of machine learning algorithms to the formatted event data;
• select the at least one machine learning algorithm from the plurality of machine learning algorithms from a data repository, the at least one machine learning algorithm selected based on a type or format of the event data;
• insert additional data associated with the event data into the computing instance, wherein insertion of the additional data causes the one or more processors to generate a modified computing instance associated with the event data, the modified computing instance configured to cause the serverless computing system to generate a modified machine learning algorithm by modifying execution of the at least one machine learning algorithm based on the additional data;
• perform, at runtime, at least one of (i) compressing the modified machine learning algorithm responsive to determining the modified machine learning algorithm exceeds a memory or computing resource restriction of the modified computing instance, or (ii) maintaining the modified machine learning algorithm responsive to determining the serverless computing system comprises a feature to automatically scale memory or computing resources;
• transmit a request to cause the serverless computing system to execute the modified computing instance using the modified machine learning algorithm;
• receive outlier data associated with the event data based on execution of the modified computing instance;
• and
• transmit, to a client device, data to cause the client device to display a graphical presentation of the outlier data.