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ModelOps
ModelOps (model operations), as defined by Gartner, "is focused primarily on the governance and life cycle management of a wide range of operationalized artificial intelligence (AI) and decision models, including machine learning, knowledge graphs, rules, optimization, linguistic and agent-based models". “ModelOps lies at the heart of any enterprise AI strategy”. It orchestrates the model life cycles of all models in production across the entire enterprise, from putting a model into production, then evaluating and updating the resulting application according to a set of governance rules, including both technical and business KPI's. It grants business domain experts the capability to evaluate AI models in production, independent of data scientists. A Forbes article promoted ModelOps: "As enterprises scale up their AI initiatives to become a true Enterprise AI organization, having full operationalized analytics capability puts ModelOps in the center, connecting both DataOps and D ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MLOps
MLOps or ML Ops is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently. The word is a compound of "machine learning" and the continuous development practice of DevOps in the software field. Machine learning models are tested and developed in isolated experimental systems. When an algorithm is ready to be launched, MLOps is practiced between Data Scientists, DevOps, and Machine Learning engineers to transition the algorithm to production systems. Similar to DevOps or DataOps approaches, MLOps seeks to increase automation and improve the quality of production models, while also focusing on business and regulatory requirements. While MLOps started as a set of best practices, it is slowly evolving into an independent approach to ML lifecycle management. MLOps applies to the entire lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gartner
Gartner, Inc is a technological research and consulting firm based in Stamford, Connecticut that conducts research on technology and shares this research both through private consulting as well as executive programs and conferences. Its clients include large corporations, government agencies, technology companies, and investment firms. In 2018, the company reported that its client base consisted of over 12,000 organizations in over 100 countries. As of 2022, Gartner has over 15,000 employees located in over 100 offices worldwide. It is a member of the S&P 500. History Gideon Gartner founded Gartner, Inc in 1979. Originally private, the company launched publicly as Gartner Group in 1986 before Saatchi & Saatchi acquired it in 1988. In 1990, Gartner Group was acquired by some of its executives, including Gartner himself, with funding from Bain Capital and Dun & Bradstreet. The company went public again in 1993. In 2000, the name was simplified from ''Gartner Group'' to G ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Forbes
''Forbes'' () is an American business magazine owned by Integrated Whale Media Investments and the Forbes family. Published eight times a year, it features articles on finance, industry, investing, and marketing topics. ''Forbes'' also reports on related subjects such as technology, communications, science, politics, and law. It is based in Jersey City, New Jersey. Competitors in the national business magazine category include '' Fortune'' and ''Bloomberg Businessweek''. ''Forbes'' has an international edition in Asia as well as editions produced under license in 27 countries and regions worldwide. The magazine is well known for its lists and rankings, including of the richest Americans (the Forbes 400), of the America's Wealthiest Celebrities, of the world's top companies (the Forbes Global 2000), Forbes list of the World's Most Powerful People, and The World's Billionaires. The motto of ''Forbes'' magazine is "Change the World". Its chair and editor-in-chief is St ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
DevOps
DevOps is a set of practices that combines software development (''Dev'') and IT operations (''Ops''). It aims to shorten the systems development life cycle and provide continuous delivery with high software quality. DevOps is complementary to agile software development; several DevOps aspects came from the ''agile'' way of working. Definition Other than it being a cross-functional combination (and a portmanteau) of the terms and concepts for "development" and "operations", academics and practitioners have not developed a universal definition for the term "DevOps". Most often, DevOps is characterized by key principles: shared ownership, workflow automation, and rapid feedback. From an academic perspective, Len Bass, Ingo Weber, and Liming Zhu—three computer science researchers from the CSIRO and the Software Engineering Institute—suggested defining DevOps as "a set of practices intended to reduce the time between committing a change to a system and the change being pla ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Time Series
In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. A time series is very frequently plotted via a run chart (which is a temporal line chart). Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements. Time series ''analysis'' comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series ''for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Metamodeling
A metamodel or surrogate model is a model of a model, and metamodeling is the process of generating such metamodels. Thus metamodeling or meta-modeling is the analysis, construction and development of the frames, rules, constraints, models and theories applicable and useful for modeling a predefined class of problems. As its name implies, this concept applies the notions of meta- and modeling in software engineering and systems engineering. Metamodels are of many types and have diverse applications. Overview A metamodel/ surrogate model is a model of the model, i.e. a simplified model of an actual model of a circuit, system, or software like entity. Metamodel can be a mathematical relation or algorithm representing input and output relations. A model is an abstraction of phenomena in the real world; a metamodel is yet another abstraction, highlighting properties of the model itself. A model conforms to its metamodel in the way that a computer program conforms to the gram ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mathematical Optimization
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maxima and minima, maximizing or minimizing a Function of a real variable, real function by systematically choosing Argument of a function, input values from within an allowed set and computing the Value (mathematics), value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, op ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Model Transformation
A model transformation, in model-driven engineering, is an automated way of modifying and creating models. An example use of model transformation is ensuring that a family of models is consistent, in a precise sense which the software engineer can define. The aim of using a model transformation is to save effort and reduce errors by automating the building and modification of models where possible. Overview Model transformations can be thought of as programs that take models as input. There is a wide variety of kinds of model transformation and uses of them, which differ in their inputs and outputs and also in the way they are expressed. A model transformation usually specifies which models are acceptable as input, and if appropriate what models it may produce as output, by specifying the metamodel to which a model must conform. Classification of model transformations Model transformations and languages for them have been classified in many ways. Some of the more common dis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
