What Is Machine Learning?

Machine learning is a process that enables computers to learn autonomously by identifying patterns and making data-based decisions. This approach is particularly useful in situations where it is impractical to write detailed instructions for every possible scenario. Many expert systems (programs that solve problems that normally require human expertise) and data mining programs (which discover useful patterns in large volumes of data) use machine learning to improve their algorithms. Though machine learning is closely related to artificial intelligence, the terms are not equivalent. By using machine learning, a computer may attain some level of artificial intelligence.

The most popular tools used in machine learning are artificial neural networks and genetic algorithms. Artificial neural networks mimic the way the human brain operates, using weighted decision paths to process information. Genetic algorithms, on the other hand, simulate the process of natural selection, in which symbols are “bred” and refined by algorithms to create increasingly effective programs. These methods allow machine learning systems to adapt and improve over time.

Machine learning is used in multiple fields, well beyond its traditional applications in expert systems and data mining. For example, many image classification systems use machine learning, in which specialized neural networks, such as convolutional neural networks (CNNs), are trained to recognize and categorize images. Additionally, machine learning is used to develop safe autonomous vehicles, improving the algorithms that enable these vehicles to navigate complex environments safely.