197 - Light GBM vs XGBoost for semantic image segmentation

Code generated in the video can be downloaded from here:
github.com/bns...
The dataset used in this video can be downloaded from the link below. This dataset can be used to train and test machine learning algorithms designed for multiclass semantic segmentation. Please read the Readme document for more information.
drive.google.c...
Note: Annotate images at www.apeer.com to create labels.
XGBoost documentation:
xgboost.readth...
lightgbm.readt...
pip install lightgbm

[@shawnirwin6633]

I have occasionally been posting links to your tutorials on my Facebook feed and Linkedin feed, because I think these tutorials are outstanding, and hopefully it will get you more subscribers. I have already been able to use what I learned so far to clean up some old photos . . . amazingly enough, a Harris filter works very well for removing spots on old photos!

[@niluparupasinghe6345]

Great as always. Thank you.

[@HuggyPandas]

oh！nice t-shirt！i will buy one！

[@vulnerablegrowth3774]

In what scenario would you use either of these methods for satellite semantic segmentation if we have Unets or other deep learning models? Maybe for your ensemble model?

[@saritagautam9328]

hello Sir! i am facing some issues while running vgg16 with XGboost. i have checked all the constraints, but my accuracy is 0.0 Please help me out.

[@rohinigaikar4117]

Hi, thank you for the video. I just want to know how this will work to give actual segmented or overlapped area in images.

[@greendsnow]

Does LGM dark boosting overfit???
I'm kind of anxious about using it. It's too much magic.

[@abdulmeral4811]

it is great thank you very much,
can you upload the .py file,
and i want to build a cbir system, (feature extraction and search algorithm)
what kind of perpective should i use to find similarity query image and dataset_images?
what do you suggest about it?
thank you very much

[@willw4096]

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