Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as “training data,” in order to make predictions or decisions without being explicitly programmed to do so.
Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. ML algorithms are used in a wide variety of applications, such as email filtering, fraud detection, and computer vision, where conventional algorithms cannot perform as well or dynamically. While machine learning has been around since the 1950s, recent breakthroughs in low-cost cloud storage and processing, easier data collection, and the proliferation of data science frameworks and libraries, have made ML much more widely used.
ML algorithms learn by example, and then apply those self-learning algorithms to uncover insights, determine relationships, and make predictions about future trends. There are several categories of machine learning, largely depending on the nature of the feedback available to the learning system:
Machine learning is considered a discipline within the broader category of artificial intelligence.