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Experimental optimizationCogneato is a tool for experimental optimization. Optimization, here, means finding the best configuration or parameter settings of a system. Experimental means that it can take significant time to evaluate any given configuration. You evaluate a configuration by measuring some business or technical metric. For example: A measurement could take minutes, hours, days, or even longer so it is important that you take as few as possible. Minimizing the number of measurements requires careful planning, called experiment design. Using Cogneato for experimental optimization works like this: Cogneato provides expertise in experiment design and statistical analysis of measurements. The user brings their domain expertise to bear on measurement and decision-making (in the analysis step). Below are some examples of experimental optimization, specifically Bayesian optimization and A/B testing, applied across diverse domains. Many methods have been developed to tackle this problem in engineering and business contexts. Among them are A/B testing, DoE, RSM, and Bayesian optimization. You can learn more from this book:
Use casesSoftware engineering
Hardware Engineering
Simulation
Materials Science
Science
Medicine
Machine learning, hyperparameter tuning
Internet productsEach link below points to information about the company's experimentation platform. |
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