vcadillog / Ensemble-Deep-Learning-Melanoma-Competition-Pytorch

Ensemble-Deep-Learning-Melanoma-Competition-Pytorch

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Ensemble-Deep-Learning-Melanoma-Competition-Pytorch

Adaptation for learning of Ensemble Neural Network of the Kaggle competition winner code and solution in a Jupyter Notebook.

Has been added:

  • Weight & Biases to plot the model metrics.

  • Result comparison between Ensemble Neural Networks using the metadata of the images and a Convolutional Neural Network.

The model was trained only on 2 Kfolds, 15 epochs in the preprocessed data of 256x256 size without a resize for the data augmentation to fit the Kaggle limits, modify below that consideration.

The ensemble model result has a score in the kaggle competition of:

  • Private: 0.9208 Public : 0.9241

The CNN model result has a score in the kaggle competition of:

  • Private: 0.9078 Public : 0.9158

W&B public plots: URL

  • Accuracy

  • Ensemble Network loss

  • CNN loss

  • Epochs

  • Folds

  • This work was inspired by 1st place Melanoma winners public repository :

https://github.com/haqishen/SIIM-ISIC-Melanoma-Classification-1st-Place-Solution

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Ensemble-Deep-Learning-Melanoma-Competition-Pytorch


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