1. A computer-implemented method for using machine learning to detect malicious code, the method comprising: reviewing, with a convolutional neural network, a sequence of chunks into which an input is divided, the reviewing comprising identifying, from amongst the sequence of chunks, a first chunk and a second chunk that are representative of the input as a whole; examining, using a recurrent neural network and in response to the reviewing with the convolutional neural network, the first chunk and the second chunk, the examining comprising determining, based at least on a first state of the first chunk, a second state of the second chunk; and summarizing, by the recurrent neural network, the first state and the second state by at least concatenating the first state and the second state, the first state and the second state being summarized to form an output comprising a classification indicative of a likelihood that the input includes the malicious code.