zahariesergiu/ubb-sociology-ml
Jan 2025 – Jan 2026
3 Months active
Languages Used
GitJupyter NotebookPythonipynbMarkdownNonePDFpython
Technical Skills
ClusteringCode CleanupCode FormattingCode OrganizationData AnalysisData Cleaning
zahariesergiu
PROFILE
Zahariesergiu
Sergiu Zaharie developed and maintained the zahariesergiu/ubb-sociology-ml repository, delivering end-to-end machine learning curriculum assets and robust data science workflows. He created and organized Jupyter Notebook-based lecture materials, implemented regression and classification models, and introduced clustering and neural network features using Python and Scikit-learn. Sergiu enhanced repository hygiene through code cleanup, documentation, and improved file organization, while also establishing automated grading and evaluation systems to support educational assessment. His work included preprocessing, exploratory data analysis, and model evaluation pipelines, resulting in reproducible, well-structured content that improved both instructional delivery and student outcomes through standardized, test-driven engineering practices.
Overall Statistics
Feature vs Bugs
91%Features
Repository Contributions
53Total
Bugs
3
Commits
53
Features
30
Lines of code
52,483
Activity Months3
Your Network
2 peopleShared Repositories
2
Work History
January 2026
21 Commits • 8 Features
Jan 1, 2026January 2026 Monthly Summary for zahariesergiu/ubb-sociology-ml. Focused on delivering up-to-date course materials, improving repository maintainability, and strengthening evaluation quality to drive student outcomes and operational efficiency. Key features delivered: - Task Notebooks Updates: Updated Task 2 and Task 3 notebooks to reflect latest tasks (commits 40317599c52a99d41965ac6ee0675db2f2240f7d; 4b4e152b507884bc448122e645ff7c2ce1693d8d). - Lecture content and slides: Lectures 1-6: Added Lecture content (Lecture 1) and slides for Lectures 1-6, and updated Lecture 1 slide (commits include 30efe1e063687de3a7b66d7e4d9bc6d46b1a2547; da2ed3bac7ba7309e5569101309b824ef116ee29; c20bfc12e4b19e58c5956eea544dac5551ba9480; 4af33e24480d00c8530ce9cfe9ab6f608226c7ca; 63ff22059aea165bbf1f80bb86c8f7a0557bf928; 2bb89576991e1c3021d17323b96f5da27def70f3; a34ca1c58fb7801b96e5418d7a593df21014d266; f71d2b7c148bd7b9a4bd72e0cfafa6e0884fc925). - Rename lectures: Renamed lectures metadata to reflect updated naming (commit e3aa9b5c01a73a0a1390c7761a881ea6268dba1a). - Notebook organization: Organized notebooks to improve structure (commits 7fb50e4841b79b6eb556a59ea050a35b2ba7135b; 984cef97e0ffd16f2592e6e8c6adcf5c518cd871). - Cleanup and hygiene: Remove slides folder and update .gitignore to ignore generated slides/notebooks artifacts (commits 1b90b2189e6724f0b90f27a171cb5dc9d9927f7e; 12b1feedb9efff9f8060c869d4bd0ed8079404b9). - Grading system enhancements: Added initial grading system and updated sigmoid-based grading to improve scoring (commits 0637526c7552dff201ecf62a0026e5aa565e68b8; 0e22fbf4ef1b21c9b46d65b3f3abbccd4d517ed4). - Test suite enhancements: Extend and refine test suite with additional test changes and a new test file (commits 2d188178ff280371a0e2d54fa03e536b41d71a38; 66ba303729dfd3861ada2d467b9e9dae7cdba4e4; 3b2f6cff1bab821c5e9db81cf7394c855427acb3). Major bugs fixed: - Fix CART Decision Trees Steps Bug: Fix issues in CART steps handling for decision trees as referenced in Lecture3 slide (commit 1653e068841b0be134806c744de1b3e8eace6a96). Overall impact and accomplishments: - Content is up to date, consistent, and easier to navigate for both students and instructors, reducing time-to-content and support requests. - Improvements in scoring fairness and reliability through a formal grading system and sigmoid-based adjustments. - Enhanced code quality and reliability via expanded test coverage and regression safeguards. - Reduced repo noise and improved collaboration readiness through hygiene improvements and metadata normalization. Technologies and skills demonstrated: - Python-based data science workflow, Jupyter notebooks, and slides authoring. - Version control discipline: organized commits, metadata renaming, and repository hygiene (gitignore, folder cleanup). - Evaluation design: initial grading schema with sigmoid-based scoring. - Quality assurance: extended test suite and new tests to reduce regressions.
21 Commits • 8 Features
Jan 1, 2026January 2026 Monthly Summary for zahariesergiu/ubb-sociology-ml. Focused on delivering up-to-date course materials, improving repository maintainability, and strengthening evaluation quality to drive student outcomes and operational efficiency. Key features delivered: - Task Notebooks Updates: Updated Task 2 and Task 3 notebooks to reflect latest tasks (commits 40317599c52a99d41965ac6ee0675db2f2240f7d; 4b4e152b507884bc448122e645ff7c2ce1693d8d). - Lecture content and slides: Lectures 1-6: Added Lecture content (Lecture 1) and slides for Lectures 1-6, and updated Lecture 1 slide (commits include 30efe1e063687de3a7b66d7e4d9bc6d46b1a2547; da2ed3bac7ba7309e5569101309b824ef116ee29; c20bfc12e4b19e58c5956eea544dac5551ba9480; 4af33e24480d00c8530ce9cfe9ab6f608226c7ca; 63ff22059aea165bbf1f80bb86c8f7a0557bf928; 2bb89576991e1c3021d17323b96f5da27def70f3; a34ca1c58fb7801b96e5418d7a593df21014d266; f71d2b7c148bd7b9a4bd72e0cfafa6e0884fc925). - Rename lectures: Renamed lectures metadata to reflect updated naming (commit e3aa9b5c01a73a0a1390c7761a881ea6268dba1a). - Notebook organization: Organized notebooks to improve structure (commits 7fb50e4841b79b6eb556a59ea050a35b2ba7135b; 984cef97e0ffd16f2592e6e8c6adcf5c518cd871). - Cleanup and hygiene: Remove slides folder and update .gitignore to ignore generated slides/notebooks artifacts (commits 1b90b2189e6724f0b90f27a171cb5dc9d9927f7e; 12b1feedb9efff9f8060c869d4bd0ed8079404b9). - Grading system enhancements: Added initial grading system and updated sigmoid-based grading to improve scoring (commits 0637526c7552dff201ecf62a0026e5aa565e68b8; 0e22fbf4ef1b21c9b46d65b3f3abbccd4d517ed4). - Test suite enhancements: Extend and refine test suite with additional test changes and a new test file (commits 2d188178ff280371a0e2d54fa03e536b41d71a38; 66ba303729dfd3861ada2d467b9e9dae7cdba4e4; 3b2f6cff1bab821c5e9db81cf7394c855427acb3). Major bugs fixed: - Fix CART Decision Trees Steps Bug: Fix issues in CART steps handling for decision trees as referenced in Lecture3 slide (commit 1653e068841b0be134806c744de1b3e8eace6a96). Overall impact and accomplishments: - Content is up to date, consistent, and easier to navigate for both students and instructors, reducing time-to-content and support requests. - Improvements in scoring fairness and reliability through a formal grading system and sigmoid-based adjustments. - Enhanced code quality and reliability via expanded test coverage and regression safeguards. - Reduced repo noise and improved collaboration readiness through hygiene improvements and metadata normalization. Technologies and skills demonstrated: - Python-based data science workflow, Jupyter notebooks, and slides authoring. - Version control discipline: organized commits, metadata renaming, and repository hygiene (gitignore, folder cleanup). - Evaluation design: initial grading schema with sigmoid-based scoring. - Quality assurance: extended test suite and new tests to reduce regressions.
January 2026
February 2025
7 Commits • 4 Features
Feb 1, 2025February 2025 monthly summary for zahariesergiu/ubb-sociology-ml. Key features delivered include the Neural Network Regression notebook for Task 5 with automated feature learning and broader preprocessing/tuning options, and the finalization of the Census Modeling and Clustering Notebook (Task 4) with clustering algorithms (K-Means, Hierarchical, DBSCAN) and notes on KElbowVisualizer/PCA. Also implemented project-wide modeling improvements: updated regression modeling requirements (hours-per-week target, hyperparameter tuning optional, justification required for primary metric) and introduced a standardized scoring/point system across notebooks to enable consistent evaluation. Minor housekeeping updates (e.g., Task 4 rename removing 'Draft') supported finalization. Major bugs fixed: none recorded in the provided data; the month focused on feature development, process improvements, and quality controls. Overall impact: enhanced modeling capability, better comparability of results, and clearer business value through standardized evaluation and automation. Technologies/skills demonstrated: neural networks for regression, clustering algorithms (K-Means, Hierarchical, DBSCAN), PCA, data preparation, feature experimentation, model evaluation, and documentation/standardization.
February 2025
7 Commits • 4 Features
Feb 1, 2025February 2025 monthly summary for zahariesergiu/ubb-sociology-ml. Key features delivered include the Neural Network Regression notebook for Task 5 with automated feature learning and broader preprocessing/tuning options, and the finalization of the Census Modeling and Clustering Notebook (Task 4) with clustering algorithms (K-Means, Hierarchical, DBSCAN) and notes on KElbowVisualizer/PCA. Also implemented project-wide modeling improvements: updated regression modeling requirements (hours-per-week target, hyperparameter tuning optional, justification required for primary metric) and introduced a standardized scoring/point system across notebooks to enable consistent evaluation. Minor housekeeping updates (e.g., Task 4 rename removing 'Draft') supported finalization. Major bugs fixed: none recorded in the provided data; the month focused on feature development, process improvements, and quality controls. Overall impact: enhanced modeling capability, better comparability of results, and clearer business value through standardized evaluation and automation. Technologies/skills demonstrated: neural networks for regression, clustering algorithms (K-Means, Hierarchical, DBSCAN), PCA, data preparation, feature experimentation, model evaluation, and documentation/standardization.
January 2025
25 Commits • 18 Features
Jan 1, 2025January 2025 (2025-01) - zahariesergiu/ubb-sociology-ml: Delivered end-to-end curriculum assets and data-science tasks, improved repository hygiene, and expanded modeling capabilities. Key outcomes include comprehensive lecture materials (Lectures 1–4 with slides and notebooks), reorganized content for usability, and end-to-end Final Project work (Census data preprocessing, EDA, and Regression Modeling). Added obesity classifier feature and task/requirements updates. These efforts accelerate teaching, enable reproducible analyses, and strengthen data handling pipelines.
25 Commits • 18 Features
Jan 1, 2025January 2025 (2025-01) - zahariesergiu/ubb-sociology-ml: Delivered end-to-end curriculum assets and data-science tasks, improved repository hygiene, and expanded modeling capabilities. Key outcomes include comprehensive lecture materials (Lectures 1–4 with slides and notebooks), reorganized content for usability, and end-to-end Final Project work (Census data preprocessing, EDA, and Regression Modeling). Added obesity classifier feature and task/requirements updates. These efforts accelerate teaching, enable reproducible analyses, and strengthen data handling pipelines.
January 2025
Activity
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Quality Metrics
Correctness94.0%
Maintainability93.6%
Architecture92.8%
Performance91.8%
AI Usage21.2%
Skills & Technologies
Programming Languages
GitJupyter NotebookMarkdownNonePDFPythonipynbpython
Technical Skills
ClusteringCode CleanupCode FormattingCode OrganizationData AnalysisData CleaningData ModelingData PreprocessingData ScienceData StructuresData TransformationData VisualizationDecision TreesDeep LearningDocumentation
Repositories Contributed To
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