{"id":20498193,"url":"https://github.com/tameronline/classification-with-transfer-learning","last_synced_at":"2025-08-26T00:10:08.319Z","repository":{"id":258425770,"uuid":"873906753","full_name":"TamerOnLine/Classification-with-Transfer-Learning","owner":"TamerOnLine","description":"Image classification using transfer learning with VGG16 on the CIFAR-10 dataset, implemented with TensorFlow and Keras.","archived":false,"fork":false,"pushed_at":"2024-10-16T23:43:21.000Z","size":6,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-16T06:38:33.994Z","etag":null,"topics":["ai","classification-internal","deep-learning","machine-learning","python"],"latest_commit_sha":null,"homepage":"https://tameronline.github.io/Classification-with-Transfer-Learning/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/TamerOnLine.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-16T23:35:27.000Z","updated_at":"2024-10-16T23:46:33.000Z","dependencies_parsed_at":"2024-10-19T00:10:13.487Z","dependency_job_id":null,"html_url":"https://github.com/TamerOnLine/Classification-with-Transfer-Learning","commit_stats":null,"previous_names":["tameronline/classification-with-transfer-learning"],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TamerOnLine%2FClassification-with-Transfer-Learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TamerOnLine%2FClassification-with-Transfer-Learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TamerOnLine%2FClassification-with-Transfer-Learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TamerOnLine%2FClassification-with-Transfer-Learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TamerOnLine","download_url":"https://codeload.github.com/TamerOnLine/Classification-with-Transfer-Learning/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":242087919,"owners_count":20069722,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","classification-internal","deep-learning","machine-learning","python"],"created_at":"2024-11-15T18:13:23.487Z","updated_at":"2025-03-05T18:59:12.566Z","avatar_url":"https://github.com/TamerOnLine.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Image Classification Using Transfer Learning\n\nThis project demonstrates image classification using a pre-trained model (VGG16) through transfer learning. The CIFAR-10 dataset is used, which consists of 60,000 32x32 color images in 10 different classes.\n\n## Overview\n\nIn this project, we leverage the power of transfer learning by using the VGG16 model, pre-trained on the ImageNet dataset, to classify images from the CIFAR-10 dataset. The final layers of the model are fine-tuned to fit our classification task.\n\n## Dataset\n\nThe CIFAR-10 dataset is used in this project. It includes the following:\n- 50,000 training images\n- 10,000 test images\n- 10 classes: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck\n\n## Model Architecture\n\n- **Base Model**: VGG16 pre-trained on ImageNet\n- **Fine-tuned Layers**: The last layers of VGG16 are replaced with fully connected layers tailored for the CIFAR-10 classification task.\n- **Optimizer**: Adam\n- **Loss Function**: Categorical Crossentropy\n\n## Data Preprocessing\n\n- Resizing images to 32x32 pixels to fit the model's input requirements.\n- One-hot encoding of the labels.\n- Data augmentation using rotation, zoom, shift, and flip techniques to prevent overfitting.\n\n## Training\n\n- **Batch size**: 64\n- **Epochs**: 25\n- **Callbacks**: Early stopping and model checkpointing are used to save the best model and avoid overfitting.\n- **Data Augmentation**: Applied to enhance the model's ability to generalize.\n\n## Results\n\nThe model achieved the following performance metrics:\n- **Training Accuracy**: `XX%`\n- **Validation Accuracy**: `XX%`\n- **Training Loss**: `XX`\n- **Validation Loss**: `XX`\n\n## Installation\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/YourUsername/YourRepoName.git\n   ```\n2. Install the dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n## Usage\n\nTo run the model training, use the following command:\n```bash\npython train_model.py\n```\n\nYou can find the saved model and training logs in the `models/` directory.\n\n## Conclusion\n\nThis project demonstrates how transfer learning can be effectively used for image classification tasks. By leveraging pre-trained models, we achieve high accuracy with less computational power and time.\n\n## License\n\nThis project is licensed under the MIT License.\n\n## Acknowledgments\n\n- The [CIFAR-10 dataset](https://www.cs.toronto.edu/~kriz/cifar.html)\n- [TensorFlow](https://www.tensorflow.org/)\n- [Keras](https://keras.io/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftameronline%2Fclassification-with-transfer-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftameronline%2Fclassification-with-transfer-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftameronline%2Fclassification-with-transfer-learning/lists"}