Image Data Classification for Skin Cancer Detection Project
OtherImageClassification
I developed a production-grade image classification pipeline using Python and deep learning frameworks. The work involved systematic evaluation and modular architecture for accurately categorizing thousands of medical images for skin cancer detection. I applied object-oriented principles to separate data ingestion, preprocessing, and inference for ease of maintainability and reproducibility.
• Classified medical images for skin cancer detection using Python, TensorFlow, and PyTorch.
• Created reproducible workflows for image data preprocessing and inference using Docker.
• Evaluated models systematically to ensure labeling accuracy and robustness.
• Ensured clear code documentation and maintainable data pipelines throughout the project.
I developed a production-grade image classification pipeline using Python and deep learning frameworks. The work involved systematic evaluation and modular architecture for accurately categorizing thousands of medical images for skin cancer detection. I applied object-oriented principles to separate data ingestion, preprocessing, and inference for ease of maintainability and reproducibility. • Classified medical images for skin cancer detection using Python, TensorFlow, and PyTorch. • Created reproducible workflows for image data preprocessing and inference using Docker. • Evaluated models systematically to ensure labeling accuracy and robustness. • Ensured clear code documentation and maintainable data pipelines throughout the project.
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