Tutorial 126 - Using pretrained deep learning model as feature extractor for XGBoost classification

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  • Опубликовано: 15 янв 2025

Комментарии • 8

  • @masroorahmedkorejo6834
    @masroorahmedkorejo6834 Год назад +1

    Thank you for great informative video It is requested that kindly make video using multiple pretrained models based on ensemble learning such as Voting, Bagging, Boosting and Stacking for image classification or detection. Thank you

  • @nasifosmanshuvra8607
    @nasifosmanshuvra8607 2 года назад

    Thank you, sir! Great! I have used the Image data generator to generate batches (16/32) of images! How can I provide the batches to xgb classifier for accomodating all the images and labels to fit with the model ??

  • @yusufbekyuldashev6776
    @yusufbekyuldashev6776 2 года назад

    Hi, sir. Thank you for this great video series. Will there be the continuations of this series?

  • @scientificstudylab1397
    @scientificstudylab1397 2 года назад

    That's great! Many thanks

  • @tilkesh
    @tilkesh 2 года назад

    Thank you very much

  • @masbro1901
    @masbro1901 2 года назад

    i use experiment data, it ran out of memory if i use 256, so i use 128 and it works.

    • @ZEISS_arivis
      @ZEISS_arivis  2 года назад

      Of course, your system memory dictates the amount of data you can work with.