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🩺 Advanced neural network for breast cancer classification using Wisconsin dataset. Analyzes cell nucleus characteristics from FNA samples to distinguish malignant/benign masses with 96.5% accuracy. Features comprehensive documentation, automated setup, testing framework, and deployment guides. Educational ML project with 15,000+ lines of docs.
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22
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docs: enhance README with comprehensive project overview and features
5e14862View on GitHubfeat: add comprehensive automated setup script for project environment
bca6f57View on GitHubfeat: add comprehensive production dependencies with version constraints
18cbe45View on GitHubfeat: add comprehensive development dependencies for complete ML workflow
55b7de2View on GitHubdocs: add detailed project structure guide with navigation tips
86e76baView on GitHubdocs: add comprehensive API documentation with complete reference
fbfd723View on GitHubdocs: add comprehensive contribution guidelines and development setup
4bbe83cView on GitHubdocs: add comprehensive FAQ covering technical and medical aspects
919bbd7View on GitHubdocs: add comprehensive deployment guide from local to cloud platforms
e15a9adView on GitHubdocs: add comprehensive testing guide with framework and best practices
02a7d20View on GitHubdocs: add comprehensive project summary with complete technical overview
b1d22a8View on GitHubdocs: enhance README with comprehensive project overview and quick start guide
a6a274dView on GitHubdocs: add comprehensive changelog with version history and project milestones
9b3057aView on GitHubdocs: Add comprehensive TensorFlow learning guide covering deep learning fundamentals to production deployment
4e9192dView on GitHub