Interactive federated learning tutorial using Flower and TensorFlow on a synthetic malaria dataset. Includes neural network customization, client simulation, and privacy-preserving collaborative training. Developed for the Women in AI Nigeria Workshop.
# federated-learning-tutorial-WAI-Virtual-Workshop
Interactive federated learning tutorial using Flower and TensorFlow on a synthetic malaria dataset. Includes neural network customization, client simulation, and privacy-preserving collaborative training. Developed for the Women in AI Nigeria Workshop.
Federated Learning Tutorial: Malaria Diagnosis
Interactive federated learning tutorial using Flower, TensorFlow, and a synthetic malaria dataset. Developed for the Women in AI Nigeria Workshop.
# You can open the notebook for the federated learning by clicking on the COLAB BADGE BELOW. It will take you directly to google colab
.ipynb)
Features
- Simulate multiple clinics (clients) collaboratively training a malaria diagnosis model.
- Customizable neural network architectures using interactive widgets.
- Privacy-preserving federated learning using Flower.
- Performance visualization and final evaluation.
How to Use
1. Open the notebook in Google Colab.
2. Upload the malaria dataset CSV to `/your/storage location/` as specified in the notebook.
3. Run all cells step-by-step.
4. Adjust architecture and client settings using the widgets.
Files
| File Name | Description |
|----------------------------------------------------|----------------------------------------------------|
| `malaria_federated_flower_colab_interactive_full.ipynb` | Interactive Colab notebook. |
| `README.md` | Project overview and usage instructions. |
| `LICENSE` | Project license (MIT). |
# Other Application Areas
1. Healthcare
2. Agriculture
3. Finance
4. Cultural AI
5. IOT
6. Cyber Security
7. Smart Cities Traffic
8. Retail
9. Education
# Note that the other datasets uploaded can also be used with the notebook uploade. You just need to replace the dataset.
Lice …