There are many practical examples of unsupervised learning. Because it enables programs to learn gaming rules and winning strategies, it’s a lucrative application for the stock market. Forecasters can use the raw data of stock prices for a program to recognize certain exchange activities and foresee trends.
Artificial intelligence, and unsupervised learning in particular, are also widely used across many other sectors. Clustering allows for the aggregation of groups of people, which is of great significance for marketing. The target group acts as the center and the basis for the creation of an advertising strategy. Algorithms can then learn how to aggregate a specific target group.
One sector in which the principle of unsupervised learning is securely anchored is speech recognition. Assistance programs such as Siri, Alexa, and Google Assistant rely on speech recognition to work effectively. These programs learn the speech patterns of their owners, and, over time, are able to understand more precise speech input, even if a device owner makes a mistake when speaking or speaks with a strong dialect.
Many smartphones also rely on unsupervised learning to help users organize their photo galleries. Through autonomous and unsupervised learning, the device is able to recognize the same person across multiple pictures or determine similarities in location where photos were taken from the metadata. As such, pictures can be organized either by location or by the people who are shown in the pictures.
Unsupervised learning is also valuable when it comes to online chats. Many Internet users have already come across chatbots, which are now used to regulate virtual conversations. Bots can also recognize insults, hate speech, and racist and discriminatory statements, and either remove the offensive user from a chat or send them a warning. Automated chats work in much the same way for applications like customer service and online orders. Whether customers use a messenger or their phone, the bots learn autonomously and sometimes even unsupervised.