302 - Tuning deep learning hyperparameters​ using GridSearchCV

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  • Опубликовано: 2 окт 2024
  • Tuning deep learning hyperparameters using Gridsearch
    Code generated in the video can be downloaded from here:
    github.com/bns...
    All other code:
    github.com/bns...
    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: www.kaggle.com...

Комментарии • 15

  • @Anil-io
    @Anil-io Год назад

    I needed this video ! Currently working on finding defects in leather seat but was having trouble finding the optimal values for the hyperparameters. this will save the day ! Thank you !

  • @pedroramon3942
    @pedroramon3942 Год назад +8

    The tensorflow.keras.wrappers are depreciated and it is recommended to use scikeras package instead.

    • @paromitakundu4034
      @paromitakundu4034 6 месяцев назад +2

      i have used scikeras to use keras classifier. but i am getting errors."ValueError: Invalid parameter neurons for estimator KerasClassifier.
      This issue can likely be resolved by setting this parameter in the KerasClassifier constructor:
      KerasClassifier(neurons=2)
      Check the list of available parameters with estimator.get_params().keys()"

    • @darrentan271
      @darrentan271 3 месяца назад

      I have the same problem too

    • @MH-ny3sd
      @MH-ny3sd 10 дней назад

      It doesn’t work for me too, I can’t do it.

  • @AbdulSyed-y8z
    @AbdulSyed-y8z 6 месяцев назад

    Thank you. You are sharing your precious knowledge, its really helpful.

  • @JovitaLewis
    @JovitaLewis Месяц назад

    great video. can you make a video on hyperparameter tuning on custom data for yolov8 model?

  • @SonGoku-rl9qf
    @SonGoku-rl9qf 3 месяца назад

    Guys why is the validation loss not monitored? I can not see it in his video. Is the accuracy calculated by the validation set?

  • @muhammad529
    @muhammad529 Год назад +1

    Hope U r doing good sir.
    Thanks a lot for ur wonderful lectures.
    Sir i m a research scholar pursuing PhD.
    Sir I face issues in using GPU of my laptop for image processing.
    Sir i have gone through all steps u mentioned like cuda, cudnn, py37env...
    Support needed.
    Thank you sir.

  • @shubhamverma8610
    @shubhamverma8610 4 месяца назад

    to search optimum parameter total no of epochs are 18*3*2*number of epochs what is 2 here?

  • @SanobarAkbarova-t4e
    @SanobarAkbarova-t4e 21 день назад

    why you didn't split data into train and test?

  • @kumargie
    @kumargie 9 месяцев назад

    Sir, can you upload the video on how to perform hyperparameter tuning using cuckoo search algorithm in deep learning architecture

  • @muhammadtahirnaseem1448
    @muhammadtahirnaseem1448 Год назад

    Excellent videos. Sir, I am working on image registration (IR and RGB) and facing some issues. How can I contact you?

  • @abdogassar9246
    @abdogassar9246 Год назад

    Great always, thank you Sir.