design-of-experiments
Expert guidance for Design of Experiments (DOE) in Python - interactive goal-driven design selection, classical DOE (factorial, response surface, screening), Bayesian optimization with Gaussian processes, model-driven optimal designs, active learning, and sequential experimentation; includes pyDOE3, pycse, BoTorch, Ax, scikit-optimize, statsmodels
Installation and usage
Expert guidance for Design of Experiments (DOE) in Python - interactive goal-driven design selection, classical DOE (factorial, response surface, screening), Bayesian optimization with Gaussian processes, model-driven optimal designs, active learning, and sequential experimentation; includes pyDOE3, pycse, BoTorch, Ax, scikit-optimize, statsmodels
انسٹال کرنے کے بعد، آپ یہ اسکل ٹرمینل میں درج ذیل کمانڈ چلا کر استعمال کر سکتے ہیں:
skills use design-of-experiments