CUAI-CAU/2025_Basic_Track_Assignment
Mar 2025 – May 2025
3 Months active
Languages Used
Jupyter NotebookPython
Technical Skills
ClusteringCross-validationData AnalysisData CleaningData PreprocessingData Science
mireurereu
PROFILE
Mireurereu
Iraesh developed a suite of machine learning resources for the CUAI-CAU/2025_Basic_Track_Assignment repository, focusing on reproducible Jupyter notebooks and hands-on curriculum materials. Over three months, Iraesh delivered end-to-end workflows covering data preprocessing, exploratory analysis, and model development using Python, NumPy, and scikit-learn. The work included practical examples in regression, classification, clustering, and ensemble learning, with clear demonstrations of feature engineering, hyperparameter tuning, and evaluation techniques. By emphasizing reproducibility and clarity, Iraesh established a scalable foundation for onboarding and future curriculum enhancements, enabling learners to quickly grasp core data science concepts through well-documented, self-contained code and experiments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
6
Lines of code
10,717
Activity Months3
Your Network
19 people
Work History
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for CUAI-CAU/2025_Basic_Track_Assignment focused on delivering end-to-end ensemble learning exploration through new Jupyter notebooks. The work established reproducible experiments across multiple ensemble methods and laid a solid baseline for evaluation and future iterations.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for CUAI-CAU/2025_Basic_Track_Assignment focused on delivering end-to-end ensemble learning exploration through new Jupyter notebooks. The work established reproducible experiments across multiple ensemble methods and laid a solid baseline for evaluation and future iterations.
May 2025
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary: Delivered a self-contained ML tutorial notebook within CUAI-CAU/2025_Basic_Track_Assignment, illustrating end-to-end ML workflows through regression and classification models. Key models covered include Ridge, Lasso, ElasticNet regression and Logistic Regression classification, with data scaling and hyperparameter tuning to show practical ML pipelines.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary: Delivered a self-contained ML tutorial notebook within CUAI-CAU/2025_Basic_Track_Assignment, illustrating end-to-end ML workflows through regression and classification models. Key models covered include Ridge, Lasso, ElasticNet regression and Logistic Regression classification, with data scaling and hyperparameter tuning to show practical ML pipelines.
March 2025
7 Commits • 4 Features
Mar 1, 2025March 2025 | CUAI-CAU/2025_Basic_Track_Assignment: Delivered a compact set of learner resources and ML notebooks enabling end-to-end practice and curriculum delivery. Four features completed across course materials and notebooks with clear documentation and reproducible code. No major bugs reported this month. Results establish a scalable foundation for onboarding and future curriculum enhancements.
7 Commits • 4 Features
Mar 1, 2025March 2025 | CUAI-CAU/2025_Basic_Track_Assignment: Delivered a compact set of learner resources and ML notebooks enabling end-to-end practice and curriculum delivery. Four features completed across course materials and notebooks with clear documentation and reproducible code. No major bugs reported this month. Results establish a scalable foundation for onboarding and future curriculum enhancements.
March 2025
Activity
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Quality Metrics
Correctness84.6%
Maintainability82.2%
Architecture82.2%
Performance80.0%
AI Usage24.6%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
ClassificationClusteringCross-validationData AnalysisData CleaningData PreprocessingData ScienceData VisualizationDecision TreesEnsemble LearningFeature EngineeringGradient DescentHyperparameter TuningJupyter NotebookK-Means
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