Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. It evolved from the study of pattern recognition and computational learning theory in artificial intelligence. Machine learning focuses on the study of algorithms that can learn from data and make predictions (or decisions) based on models built from sample inputs.
Machine learning also refers to a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. The ability to automatically apply complex mathematical calculations to big data has led to the development of machine learning applications such as self-driving cars, online shopping recommendations, email filtering, intruder prevention, fraud detection and natural language interfaces.
Machine learning is closely related to computational statistics, which also uses computer prediction-making. The growing volumes and varieties of available data, cheaper compute processing and more affordable data storage are driving new demands for machine learning. Enterprises are looking for ways to quickly and automatically produce models that can analyze more complex data and deliver more accurate results, thereby identifying new opportunities or avoiding risks. Using machine learning to build predictive models can help organizations make data-driven decisions without human intervention. A supercomputer or high performance computing (HPC) infrastructure is generally required to build machine learning applications. SUSE Linux Enterprise High Performance Computing allows companies to leverage underlying hardware to power their machine learning applications and data analysis.