Identify American Express customers most likely to default in the next 3 months based on 190 anonymized transaction data features for over 500000 American Express customers.
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Updated
Sep 18, 2022 - Python
Identify American Express customers most likely to default in the next 3 months based on 190 anonymized transaction data features for over 500000 American Express customers.
PyTorch implementation of focal loss for multi-class semantic segmentation
📦Simple Tool Box with Pytorch
Adversarial Focal Loss: Asking Your Discriminator for Hard Examples.
Alternative loss function of binary cross entropy and focal loss
Classification for SMS Spam Collection Dataset using BERT
Feed Forward Neural network: Implemented for bond fluctuation model utilities.
PyTorch implementation of focal loss for dense object detection
SAFL: A Self-Attention Scene Text Recognizer with Focal Loss (ICMLA20)
Here I solved the problem classification of the skin lesions.
Imbalanced classification with scikit-learn and PyTorch Lightning.
Pytorch implementation of Class Balanced Loss based on Effective number of Samples
A Fully Convolutional Network for car sergmentation
Implementation of some basic Image Annotation methods (using various loss functions & threshold optimization) on Corel-5k dataset with PyTorch library
KL severity grading using SE-ResNet and SE-DenseNet architectures trained with Cross Entropy loss and Focal Loss. The hyperparameters of focal loss have been fine-tuned as well. Further, Grad-CAM has been implemented for visualization purposes.
Classification of Ionosphere dataset using pytorch neural networks.
PyTorch implementation of RetinaNet with the goal to reproduce results in the "focal loss for dense object detection" paper.
Covid19 X-ray Images Classification, Imbalanced Data using Transfer Learning, Focal Loss
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