AI vs. ML vs. DL
Artificial intelligence (AI) is the broadest term of the three. AI consists of everything related to making machines smart and capable of thinking without human intervention. The overall goal of AI is to allow computers to perform cognitive tasks in a wide range of areas like a human would.
Machine learning (ML) is a subset of AI. The main idea here is to create algorithms that can learn how to make decisions by themselves. For example, in the table below, we are deciding if we’d play tennis based on some features (outlook, temperature, humidity, and wind). In ML, we’d give this data to the model and let it learn how the decision is being made. Then we would have the model independently make the decision once we find only the features without the label (yes/no).
Deep learning (DL) is a subset of ML. DL algorithms mimic the processing patterns in the human brain by creating artificial neural networks consisting of several different layers of neurons. These algorithms require more data than ML algorithms.
