Machine learning is the subset of artificial intelligence (AI) that focuses on building systems that learn—or improve performance—based on the data they consume. Artificial intelligence is a broad term that refers to systems or machines that mimic human intelligence. Machine learning and AI are often discussed together, and the terms are sometimes used interchangeably, but they don’t mean the same thing. An important distinction is that although all machine learning is AI, not all AI is machine learning.
Today, machine learning is at work all around us. When we interact with banks, shop online, or use social media, machine learning algorithms come into play to make our experience efficient, smooth, and secure. Machine learning and the technology around it are developing rapidly, and we’re just beginning to scratch the surface of its capabilities.
Two Approaches to Learning
Algorithms are the engines that power machine learning. In general, two major types of machine learning algorithms are used today: supervised learning and unsupervised learning. The difference between them is defined by how each learns about data to make predictions.