Скачать с ютуб 302 - Tuning deep learning hyperparameters​ using GridSearchCV в хорошем качестве

302 - Tuning deep learning hyperparameters​ using GridSearchCV

Tuning deep learning hyperparameters using Gridsearch Code generated in the video can be downloaded from here: https://github.com/bnsreenu/python_fo... All other code: https://github.com/bnsreenu/python_fo... The grid search provided by GridSearchCV exhaustively generates candidates from a grid of parameter values specified with the param_grid parameter. The GridSearchCV instance when “fitting” on a dataset, all the possible combinations of parameter values are evaluated, and the best combination is retained. cv parameter can be defined for the cross-validation splitting strategy. GridSearch is designed to work with models from sklearn. But, we can also use it to tune deep learning hyper parameters - at least for keras models. Wisconsin breast cancer example Dataset link: https://www.kaggle.com/datasets/uciml...