Strengths3
- End-to-end workflow from data to deployable API.
- Inclusion of model explainability via Grad-CAM for interpretability.
- Clear documentation and setup instructions for the inference service.
ML Application · Jupyter Notebook
Skin-Cancer-Classifier
What it is
This repository provides an end-to-end skin cancer classification system, including a CNN model trained on the Melanoma Skin Cancer Dataset, a FastAPI service for inference, and Grad-CAM visualizations for model interpretability. The model achieves approximately 90% accuracy on the evaluation set.
Merit describes the code at this commit. Later pushes count once the owner rescans. How merit is scored
Where it counts
- Machine Learning90%
- Computer Vision90%
- Data Science40%
- MLOps30%
How much of the project is about each field, as scoring counts it. It ranks in the field it is most about.
What the judge found
Read from the project's code at its scored commit.
Limitations
The owner keeps this project's limitations private.
Around it on the Machine Learning board
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- 93, shared ranksocrateLibrary / Framework · Jupyter Notebook49.2Implementationvlad andreiMachine Learning
- 93, shared rankSkin-Cancer-ClassifierML Application · Jupyter Notebook49.2Implementationkamran akmalMachine Learning
- 96fake-news-detectorML Application · Jupyter Notebook49.0Implementationkamran akmalMachine Learning
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