January 2025 monthly summary for sejongsmarcle/2025_2nd_SMARTHON: Delivered a Presentation Materials Update to support updated client/demo materials. Added a new PowerPoint asset to the repository under database/presentation materials, creating a ready-to-use non-code asset for client demos and marketing materials. This change strengthens demo readiness and ensures consistency across client-facing presentations.

Month: 2024-11 | Repository: sejongsmarcle/2024_Autumn_Machine_Learning_Study Key features delivered: - Machine Learning experiments notebooks: MNIST experiments with classifiers (Random Forest, Bagging, Voting Classifier) and a K-Means clustering notebook on Olivetti faces with PCA, inertia, and silhouette evaluation. Commits: 5618df56e0fbd3836d454ad224d59e22137d07e4; 028a164fd7a44ab85e63b1c2c8d6451d787960c2. - Documentation: Weekly assignments links: Markdown notes linking CH8 and CH9 weekly assignments. Commits: 5d226a1bb26dd08baba0f37713092c4b6cbc28fb; bc53e3c89afbb8d61b6e95ca17137dfb7cc7ce4c. Major bugs fixed: None reported this month; the focus was feature delivery and documentation. Overall impact and accomplishments: - Provides reproducible, hands-on ML materials accelerating experimentation, learning, and onboarding. - Improves project knowledge transfer with structured weekly assignment documentation. Technologies/skills demonstrated: - Python, Jupyter notebooks, scikit-learn (Random Forest, Bagging, Voting, K-Means, PCA), evaluation metrics (inertia, silhouette). - Git-based collaboration with concise commit messages and clear documentation. Business value: - Faster prototyping and assessment of ML ideas; improved onboarding and maintainability through better documentation.