Abstract: A system and method for implementing a machine learning system using dynamic multilayer perceptrons transforms input data into directed acyclic graphs. Dynamic multilayer perceptron network graphs are generated based at least in part on the directed acyclic graphs. During training of the machine learning system, a trained weight set is determined by transforming training data into directed acyclic graphs and dynamic multilayer perceptron network graphs and adjusting the weights of the dynamic multilayer perceptron network graphs. When using the machine learning system, an output value is determined by transforming subject data into a subject dynamic acyclic graph. The trained weight set and subject dynamic acyclic graph are applied to a dynamic multilayer perceptron network graph that was generated based on the subject data resulting in the output.