This example is going to help you understand machine learning and deep learning easily, have you seen how babies identify objects? They do so by their parents showing the distinguishable
features of different object. Suppose a chair, it has four legs, and mostly it's near a table.
they learn from what their parents have told them. Now imagine a machine doing the same, you feed some data into a machine and it learns from it.
"Machines can predict the future, as long as the future doesn’t look too different from the past."
How do they do this? To keep it simple machines “learn” by finding patterns in similar
data. Think of data as information you acquire from the world. The more data given to a machine, the “smarter” it gets.
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Lets go back to the example we took earlier suppose the kid is a bit mature now and he is learning to talk, how he learns talking is by observing other people, listening to them how they talk! Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost.
In order to understand the difference? between them, first we have to learn what is supervised and unsupervised learning. Supervised Learning is when we train the model by providing it with labels along the data! In Unsupervised Learning is a self-learning technique in which system has to discover the features of the input population by its own and no prior set of categories are used