https://github.com/dharma-acha/resnet18_imageclassification_cnn
In this part of the project, we implement ResNet-18 from scratch using PyTorch and train it on an image dataset to achieve over 75% accuracy. We apply techniques to prevent overfitting and optimize performance, aiming for an accuracy of 80% or higher.
https://github.com/dharma-acha/resnet18_imageclassification_cnn
matplotlib numpy python3 pytorch scikit-learn seaborn
Last synced: about 1 month ago
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In this part of the project, we implement ResNet-18 from scratch using PyTorch and train it on an image dataset to achieve over 75% accuracy. We apply techniques to prevent overfitting and optimize performance, aiming for an accuracy of 80% or higher.
- Host: GitHub
- URL: https://github.com/dharma-acha/resnet18_imageclassification_cnn
- Owner: dharma-acha
- Created: 2024-06-07T20:44:40.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-07T20:56:26.000Z (over 1 year ago)
- Last Synced: 2025-05-31T15:29:41.839Z (9 months ago)
- Topics: matplotlib, numpy, python3, pytorch, scikit-learn, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 41.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md