Deep Learning is a subset of Machine Learning that uses neural networks, significant amounts of computing power, and massive datasets to create systems that can learn independently. It can perform more complex actions than traditional Machine Learning models.

To understand Deep Learning and its differences from Machine Learning, you need to understand neural networks.

Neural networks, or more precisely, artificial neural networks, are computer systems that consist of multiple layers or nodes. Layers are small systems that are dedicated to specific types of tasks. When these layers are combined, the resulting system can learn how to tackle complex, multidimensional tasks in a way that simulates the human brain.

Deep Learning systems have at least three layers, but usually more (many have 100+ layers). In this case, "deep" refers to the multiple layers of these systems and is in contrast to less complex Machine Learning tools.