Verification and validation of computer simulation models is conducted during the development of a simulation model with the ultimate goal of producing an accurate and credible model. "Simulation models are increasingly being used to solve problems and to aid in decision-making. The developers and users of these models, the decision makers using information obtained from the results of these models, and the individuals affected by decisions based on such models are all rightly concerned with whether a model and its results are "correct". This concern is addressed through verification and validation of the simulation model. Simulation models are approximate imitations of real-world systems and they never exactly imitate the real-world system. Due to that, a model should be verified and validated to the degree needed for the model's intended purpose or application. The verification and validation of a simulation model starts after functional specifications have been documented and initial model development has been completed. Verification and validation is an iterative process that takes place throughout the development of a model. (Wikipedia).
What are the different ways to perform data validation in machine learning?
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From playlist Machine Learning
Why do we need data validation in machine learning?
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From playlist Quick Machine Learning Concepts
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From playlist Machine Learning
Keynote Presentation: Framework for Developing Complex Systems
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From playlist MathWorks Automotive Conference 2013
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Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Automatically run tests and generate a report documenting simulation results. For more videos, visit http://www.mathworks.com/products/simscape/examples.html
From playlist Physical Modeling
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https://www.turing-gateway.cam.ac.uk/sites/default/files/asset/doc/1707/Big%20Proof%20Day%20Melham%2019-07-2017.pdf #TuringSeminars
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