Before we move to discussion about deep learning. Let's understand what is machine learning. Deep learning is a subfield of machine learning.
Here is how Herbert Alexander Simon (Turning and Nobel Prize winner) defined it:
Learning is any process by which a system improves performance from experience.
Machine Learning is concerned with computer programs that automatically improve their performance through experience.
Let's have a look at a simple machine learning problem to see what it all means:
Given measurements of an unknown Iris flower's petal and sepal identify the species of the plant.
We have known information of lots of Iris flowers. This the experience that machine learning will use to improve its performance on the task of identifying species.
To see if machine learning improves on the performance we must define performance for our algorithm.
In this example a simple way to define performance would be accuracy of correct answers on a set of flowers that are not in the experience (training dataset) of machine learning algorithm.