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302 Tuning deep learning hyperparameters using GridSearchCV
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=lV0weESA0Sc
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...
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