What’s the difference between Deep Learning and Machine Learning?

Question

I see there’s a lot of confusion between the two areas.

Any real variation aside from their similarities?

In: 3

Answer 1

Deep learning is a specific *type* of machine learning. All DL is ML, but not all ML is DL.

Machine learning is a very wide field in computer science whose main concern is researching, developing, and finding use cases for… well, machines learning. Having computers not be told how to solve a given problem, but to analyze the problem and come up with solutions on their own accord. This can be with statistical methods, with neural networks, with self-modifying code, classification trees, e.t.c.

Deep Learning is, in extremely short terms, a method in which you construct a neural network (which is a data structure that aims to in a way replicate how a brain works with neurons and edges connecting those neurons) that has multiple layers (ergo, “Deep”) passing data from one layer to the next in order to transform the input data in to an output answer. The “learning” bit comes from slowly tuning the network over multiple generations until it starts doing something useful with the data we feed in instead of just echoing random nonsense.