kietmcaproject/AI_AI101B_2024-25
Apr 2025 – May 2025
2 Months active
Languages Used
PythonSQL
Technical Skills
Data PreprocessingData ScienceData VisualizationKerasMachine LearningModel Training
kumarkashyap1289
PROFILE
Kumarkashyap1289
Over a two-month period, this developer contributed to the kietmcaproject/AI_AI101B_2024-25 repository by delivering two end-to-end features focused on data-driven reporting and health analytics. They created structured Employee Salary Analysis Reporting Artifacts, including a PDF report, presentation, and code documentation, enhancing stakeholder review processes and repository organization. In the following month, they developed a Heart Disease Prediction Notebook with a real-time user interface, supporting data loading, preprocessing, and model comparison using Random Forest and Artificial Neural Network approaches. Their work demonstrated proficiency in Python, Pandas, and TensorFlow, emphasizing reproducible workflows, clear documentation, and actionable data insights.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
374
Activity Months2
Your Network
139 peopleWork History
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for developer work focusing on AI/health analytics features. Delivered a feature-rich Heart Disease Prediction Notebook with a Real-Time Interface in the AI_AI101B_2024-25 repository, enabling end-to-end experimentation from data loading to live predictions and model comparison.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for developer work focusing on AI/health analytics features. Delivered a feature-rich Heart Disease Prediction Notebook with a Real-Time Interface in the AI_AI101B_2024-25 repository, enabling end-to-end experimentation from data loading to live predictions and model comparison.
May 2025
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary: Focused on delivering structured salary analysis reporting artifacts to enable faster decision-making and stakeholder reviews. The key deliverable, Employee Salary Analysis Reporting Artifacts, includes a PDF report, a presentation, and a code-related PDF, all created and organized under the Tech Triad directory in kietmcaproject/AI_AI101B_2024-25. The work was committed in a single commit (656d38687f923a4f1267bb5b9335ceaf7300e663). No major bugs were reported or fixed this month. Overall impact: improved visibility and governance of salary analysis data, accelerated review cycles, and a strengthened documentation footprint. Technologies demonstrated: PDF report generation, presentation design, code-to-documentation packaging, and disciplined repository organization.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary: Focused on delivering structured salary analysis reporting artifacts to enable faster decision-making and stakeholder reviews. The key deliverable, Employee Salary Analysis Reporting Artifacts, includes a PDF report, a presentation, and a code-related PDF, all created and organized under the Tech Triad directory in kietmcaproject/AI_AI101B_2024-25. The work was committed in a single commit (656d38687f923a4f1267bb5b9335ceaf7300e663). No major bugs were reported or fixed this month. Overall impact: improved visibility and governance of salary analysis data, accelerated review cycles, and a strengthened documentation footprint. Technologies demonstrated: PDF report generation, presentation design, code-to-documentation packaging, and disciplined repository organization.
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
Data PreprocessingData ScienceData VisualizationKerasMachine LearningModel TrainingPandasPythonScikit-learnTensorFlow
Repositories Contributed To
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