Deep learning (DL) is a method of Machine Learning which teaches machines with as little human effort as possible. They learn from example, like humans, by digesting large amounts of data.
Unlike other other types of Machine Learning that require you to outline features to look for in the data, Deep Learning models deal directly with the data– no human intervention!
The downside to this is Deep Learning models require more data and higher computing power. Also, it takes longer to train DL models.
One of the benefits to DL models is they are more accurate. In addition, they are the best models if you don’t know the features you’re looking for in your data.
Deep Learning is accomplished using neural networks. A neural network is a computing model which is structured based on the structure of a brain.
Deep Learning is used in driverless cars, detecting cancer cells, improving worker safety around heavy machinery, in home assistants, and many other situations nowadays.
Joshua Bowen's Notes 