Whois & Analysis for proctorio.net

network security means protecting data, such as a database, from destructive forces and from the unwanted actions of unauthorized users.

Educational technology is defined by the Association for Educational Communications and Technology as "the study and ethical practice of facilitating learning and improving performance by creating, using, and managing appropriate technological processes and resources".

Data integrity is the maintenance of, and the assurance of the accuracy and consistency of, data over its entire life-cycle, and is a critical aspect to the design, implementation and usage of any system which stores, processes, or retrieves data.

The term data integrity is broad in scope and may have widely different meanings depending on the specific context even under the same general umbrella of computing.

This article provides only a broad overview of some of the different types and concerns of data integrity.

Technology ("science of craft", from Greek, techne, "art, skill, cunning of hand"; and) is the collection of techniques, skills, s and processes used in the production of goods or services or in the accomplishment of objectives, such as scientific investigation.

Technology can be the knowledge of techniques, processes, and the like, or it can be embedded in machines which can be operated without detailed knowledge of their workings.

Machine learning is the subfield of computer science that, according to Arthur Samuel in 1959, gives "computers the ability to learn without being explicitly programmed." Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data – such algorithms overcome following strictly static program instructions by making data driven predictions or decisions, through building a model from sample inputs.

Machine learning is employed in a range of computing tasks where designing and programming explicit algorithms with good performance is difficult or unfeasible; example applications include email filtering, detection of network intruders or malicious insiders working towards a data breach, optical character recognition (OCR), learning to rank and computer vision.