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

Code associated with these tutorials can be downloaded from here: github.com/bns...

[@masroorahmedkorejo6834]

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

[@scientificstudylab1397]

That's great! Many thanks

[@tilkesh]

Thank you very much

[@nasifosmanshuvra8607]

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]

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

[@ZEISS_arivis]

Hopefully soon.

[@masbro1901]

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

[@ZEISS_arivis]

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