Information engineering

_Information engineering Information engineering is the engineering discipline that deals with the generation, distribution, analysis, and use of information, data, and knowledge in systems. The field first became identifiable in the early 21st century. The components of information engineering include more theoretical fields such as machine learning, artificial intelligence, control theory, signal processing, and information theory, and more applied fields such as computer vision, natural language processing, bioinformatics, , cheminformatics, autonomous robotics, mobile robotics, and telecommunications. Many of these originate from computer science, as well as other branches of engineering such as computer engineering, electrical engineering, and bioengineering. The field of information engineering is based heavily on mathematics, particularly probability, statistics, calculus, linear algebra, optimization, differential equations, variational calculus, and complex analysis. Information engineers often hold a degree in information engineering or a related area, and are often part of a professional body such as the Institution of Engineering and Technology or Institute of Measurement and Control. They are employed in almost all industries due to the widespread use of information engineering. In the 1980s/1990s term information engineering referred to an area of software engineering which has come to be known as data engineering in the 2010s/2020s. Machine learning Machine learning is the field that involves the use of statistical and probabilistic methods to let computers "learn" from data without being explicitly programmed. Data science involves the application of machine learning to extract knowledge from data. Subfields of machine learning include deep learning, supervised learning, unsupervised learning, reinforcement learning, semi-supervised learning, and active learning. Causal inference is another related component of information engineering.