/Caltech-UCSD-Birds-PyTorch

German traffic signs dataset is analysed with Keras. This task is a multi-class classification problem and the dataset is complex because of containing 200 classes with 12000 images. The dataset is splitted into training, validation and test dataset and normalised. Data is preprocessed and data augmentation is applied. The ResNet model is used by the courtesy of transfer learning and trained. At the end of this process, 69% acurracy is obtained on the test dataset

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