ResumeRover/Main
Apr 2025 – May 2025
2 Months active
Languages Used
Jupyter NotebookPython
Technical Skills
Data CleaningData PreprocessingFeature EngineeringMachine LearningNatural Language ProcessingPandas
yugan243
PROFILE
Yugan243
Yugan Nimsara developed robust machine learning pipelines for the ResumeRover/Main repository, focusing on feature engineering and model training over a two-month period. He engineered a derived 'experience_years' feature by preprocessing and normalizing date fields, and created job title embeddings using MiniLM sentence transformers to enhance model input quality. Leveraging Python, pandas, and scikit-learn, he built notebook-driven workflows for decision tree regression, incorporating randomized grid search for hyperparameter tuning and model persistence with joblib. His work emphasized reproducible experimentation, improved data validation, and production-ready pipelines, demonstrating depth in data preprocessing, NLP feature engineering, and end-to-end machine learning deployment.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
4
Lines of code
1,614
Activity Months2
Your Network
5 people
Work History
May 2025
3 Commits • 2 Features
May 1, 2025Monthly summary for 2025-05: Two notebook-driven ML pipelines delivered in ResumeRover/Main, enabling repeatable experimentation, hyperparameter tuning, and model persistence. Key features include a Decision Tree Regressor Training Notebook with randomized grid search (data loading, train/validation/test splits, training with specified hyperparameters, evaluation via MSE and R², and saving the trained model) and AI Candidate Ranking Model Training Notebook Enhancements (refined execution counts, model parameters, and validation/test performance metrics, plus saving the best performing model). Impact centers on faster experimentation cycles, improved model quality through robust hyperparameter search, and reproducible, production-ready pipelines. Technologies demonstrated include Python, Jupyter notebooks, scikit-learn, dataset handling, model evaluation (MSE, R²), and model serialization.
3 Commits • 2 Features
May 1, 2025Monthly summary for 2025-05: Two notebook-driven ML pipelines delivered in ResumeRover/Main, enabling repeatable experimentation, hyperparameter tuning, and model persistence. Key features include a Decision Tree Regressor Training Notebook with randomized grid search (data loading, train/validation/test splits, training with specified hyperparameters, evaluation via MSE and R², and saving the trained model) and AI Candidate Ranking Model Training Notebook Enhancements (refined execution counts, model parameters, and validation/test performance metrics, plus saving the best performing model). Impact centers on faster experimentation cycles, improved model quality through robust hyperparameter search, and reproducible, production-ready pipelines. Technologies demonstrated include Python, Jupyter notebooks, scikit-learn, dataset handling, model evaluation (MSE, R²), and model serialization.
May 2025
April 2025
2 Commits • 2 Features
Apr 1, 2025Month: 2025-04 — Performance-oriented feature engineering and NLP feature engineering for ResumeRover/Main, focused on building robust, ML-ready inputs and enabling richer job-title representations.
April 2025
2 Commits • 2 Features
Apr 1, 2025Month: 2025-04 — Performance-oriented feature engineering and NLP feature engineering for ResumeRover/Main, focused on building robust, ML-ready inputs and enabling richer job-title representations.
Activity
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Quality Metrics
Correctness82.0%
Maintainability80.0%
Architecture80.0%
Performance72.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data CleaningData PreprocessingData ScienceData ValidationDecision TreesFeature EngineeringHyperparameter TuningJoblibMachine LearningModel TrainingNatural Language ProcessingPandasPythonScikit-learnSentence Transformers
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline