CUAI-CAU/2025_Basic_Track_Assignment
Mar 2025 – May 2025
3 Months active
Languages Used
Jupyter NotebookPythonJSONShell
Technical Skills
Cross-ValidationData AnalysisData CleaningData ClusteringData ManipulationData Preprocessing
jong1221
PROFILE
Jong1221
Over a three-month period, contributed to the CUAI-CAU/2025_Basic_Track_Assignment repository by developing a suite of Jupyter Notebook-based machine learning tutorials and resources. Work included building end-to-end workflows for regression, classification, and ensemble methods, with practical examples using datasets such as Titanic, Boston housing, and Iris. Applied Python, Pandas, and Scikit-learn to demonstrate model evaluation, feature engineering, dimensionality reduction with PCA, and hyperparameter tuning with HyperOpt. Enhanced repository organization through code cleanup and standardized naming, ensuring maintainability and reproducibility. These efforts provided reusable educational assets and streamlined onboarding for data science experimentation and instruction within the repository.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
19Total
Bugs
1
Commits
19
Features
7
Lines of code
30,090
Activity Months3
Your Network
19 peopleWork History
May 2025
11 Commits • 4 Features
May 1, 2025May 2025 monthly summary for CUAI-CAU/2025_Basic_Track_Assignment: Delivered a comprehensive set of ML education notebooks, enhanced code quality, and improved repository hygiene. Features delivered include model evaluation tutorials across multiple classifiers and datasets, PCA-based feature extraction, ensemble methods with HyperOpt tuning, and robust visualizations. Conducted thorough cleanup to remove outdated notebooks and standardize naming, reducing confusion and ensuring maintainability. The work delivered business value by providing reusable, well-documented learning resources and preparing the repository for scalable teaching and experimentation.
11 Commits • 4 Features
May 1, 2025May 2025 monthly summary for CUAI-CAU/2025_Basic_Track_Assignment: Delivered a comprehensive set of ML education notebooks, enhanced code quality, and improved repository hygiene. Features delivered include model evaluation tutorials across multiple classifiers and datasets, PCA-based feature extraction, ensemble methods with HyperOpt tuning, and robust visualizations. Conducted thorough cleanup to remove outdated notebooks and standardize naming, reducing confusion and ensuring maintainability. The work delivered business value by providing reusable, well-documented learning resources and preparing the repository for scalable teaching and experimentation.
May 2025
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for CUAI-CAU/2025_Basic_Track_Assignment: Key features delivered include the ML Model Tutorial Notebook: Regression and Classification with Scaling. The notebook demonstrates applying and evaluating linear regression models (Ridge, Lasso, ElasticNet) on the Boston housing dataset, explores data scaling techniques, and includes a Logistic Regression workflow for a cancer dataset, with hyperparameter tuning and performance evaluation. This work was committed in 4483ada2f15a93a504b9df6da269dd2ffbffc0f2 with the message 'Add files via upload'.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for CUAI-CAU/2025_Basic_Track_Assignment: Key features delivered include the ML Model Tutorial Notebook: Regression and Classification with Scaling. The notebook demonstrates applying and evaluating linear regression models (Ridge, Lasso, ElasticNet) on the Boston housing dataset, explores data scaling techniques, and includes a Logistic Regression workflow for a cancer dataset, with hyperparameter tuning and performance evaluation. This work was committed in 4483ada2f15a93a504b9df6da269dd2ffbffc0f2 with the message 'Add files via upload'.
March 2025
7 Commits • 2 Features
Mar 1, 2025Month: 2025-03. This month focused on delivering learning resources and Kaggle-related assets in the CUAI-CAU repository. Key features shipped include: (1) Kaggle Basic Image Resources: added binary image assets to support Kaggle basic track assignments. (2) ML Basics Tutorials and Datasets: notebooks covering NumPy basics, Pandas data handling (Titanic), core ML concepts, K-Means clustering, and regression techniques, enabling self-guided learning and reproducible experiments. No major bugs were reported or fixed in this period. Overall impact: improved onboarding, faster experiment setup, and a stronger foundation for data science workflows in the basic track. Technologies and skills demonstrated: asset management for binary resources, notebook-based teaching resources, Python stack (NumPy, Pandas, ML concepts), version control traceability, and repository organization.
7 Commits • 2 Features
Mar 1, 2025Month: 2025-03. This month focused on delivering learning resources and Kaggle-related assets in the CUAI-CAU repository. Key features shipped include: (1) Kaggle Basic Image Resources: added binary image assets to support Kaggle basic track assignments. (2) ML Basics Tutorials and Datasets: notebooks covering NumPy basics, Pandas data handling (Titanic), core ML concepts, K-Means clustering, and regression techniques, enabling self-guided learning and reproducible experiments. No major bugs were reported or fixed in this period. Overall impact: improved onboarding, faster experiment setup, and a stronger foundation for data science workflows in the basic track. Technologies and skills demonstrated: asset management for binary resources, notebook-based teaching resources, Python stack (NumPy, Pandas, ML concepts), version control traceability, and repository organization.
March 2025
Activity
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Quality Metrics
Correctness85.2%
Maintainability85.2%
Architecture84.2%
Performance84.2%
AI Usage22.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookPythonShell
Technical Skills
BaggingBoostingClassificationCross-ValidationCross-validationData AnalysisData CleaningData ClusteringData ManipulationData PreprocessingData ScienceData VisualizationDecision TreesDimensionality ReductionElasticNet Regression
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline