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precision-recall-auc-f1-score

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Manishdebnath99 / Fraud-Detection

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Detecting fraudulent financial transactions using machine learning. Includes data preprocessing, EDA, model training - Logistic Regression and evaluation using precision, recall, and ROC-AUC to build an accurate fraud detection system.

exploratory-data-analysis pandas logistic-regression matplotlib scikitlearn-machine-learning streamlit-webapp model-selection-and-evaluation precision-recall-auc-f1-score data-preprocessing-and-feature-engineering
  • Updated Aug 4, 2025
  • Jupyter Notebook

himanshumahajan138 / TransferVision

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Transfer learning for image classification using pre-trained models like ResNet50, ResNet100, EfficientNetB0, and VGG16 in Keras. Fine-tunes the last layers, applies image augmentation, and evaluates with Precision, Recall, AUC, F1 score, and early stopping for improved performance.

deep-learning keras batch-normalization image-classification regularization transfer-learning vgg16 image-augmentation multiclass-classification adam-optimizer resnet50 early-stopping data-pre-processing relu-activation efficientnetb0 resnet100 precision-recall-auc-f1-score
  • Updated Jan 9, 2025
  • Jupyter Notebook

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