PyTorch for image classification
Kukutapu Varun Kumar
Dataset: A diverse image dataset used for classification tasks.
Transfer Learning: Utilizes pre-trained models, fine-tuned for the specific dataset.
Techniques: Data preprocessing, model training, and hyperparameter tuning.
Optimization: Techniques like data augmentation and dropout were used to avoid overfitting.
Outcome: Improved accuracy and faster training times, showcasing real-world applicability.
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Posted Sep 26, 2024
Built an image classification model using PyTorch and transfer learning. Optimized performance through fine-tuning, data augmentation, and dropout.
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