The ability of computer systems to autonomously improve their performance on a specific task through experience is a rapidly developing area. This area encompasses a range of techniques that enable machines to extract patterns from data and make predictions or decisions without explicit programming for every possible scenario. For example, a system can be trained on a large dataset of images to identify specific objects, or it can analyze customer behavior to personalize recommendations.
This capability is of significant value across various sectors. It allows for automation of complex processes, improved accuracy in decision-making, and the discovery of insights hidden within large datasets. Historically, this field has evolved from rule-based systems to statistical models and, more recently, to deep learning architectures. These advancements have broadened the scope of problems that can be addressed effectively.