Method and system for performing machine learning

A non-transitory computer readable medium that stores a set of instructions that is executable by at least one processor of a computer system to cause the computer system to perform a method for simplifying a machine learning model, the method comprising:

• receiving training data;
• training a machine learning model based on the training data, wherein the machine learning model includes multiple layers each having one or more nodes having one or more connections with a node from another layer of the machine learning model;
• evaluating weights associated with the connections of the machine learning model, wherein each connection has a corresponding weight;
• removing, from the machine learning model, one or more connections having a weight that does not satisfy a threshold condition;
• evaluating layer weights associated with the layers of the machine learning model, wherein each layer has a corresponding layer weight;
• removing, from the machine learning model, one or more layers having a layer weight that does not satisfy a layer threshold condition;
• and
• after the connections and the one or more layers have been removed, updating the machine learning model.

A computer system, comprising:

• a memory storing a set of instructions;
• and
• at least one processor configured to execute the set of instructions to cause the system to perform:
• receiving training data;
• training a machine learning model based on the training data, wherein the machine learning model includes multiple layers each having one or more nodes having one or more connections with a node from another layer of the machine learning model;
• evaluating weights associated with the connections of the machine learning model, wherein each connection has a corresponding weight;
• removing, from the machine learning model, one or more connections having a weight that does not satisfy a threshold condition;
• evaluating layer weights associated with the layers of the machine learning model, wherein each layer has a corresponding layer weight;
• removing, from the machine learning model, one or more layers having a layer weight that does not satisfy a layer threshold condition;
• and
• after the connections and the one or more layers have been removed, updating the machine learning model.