springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction
Dec 2024 – Dec 2024
1 Month active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
Code CleanupData ScienceData VisualizationDocumentationForecastingGrid Search
Bhavajna-Madivada
PROFILE
Bhavajna-madivada
Worked on the FutureCart--AI-Driven-Demand-Prediction repository, delivering a grid-search based Ridge regression workflow for multivariate demand forecasting. Leveraged Python, Pandas, and Scikit-learn to implement hyperparameter tuning, evaluate models using RMSE, and visualize forecast results for stakeholders. Developed and organized demo assets, including presentation slides and a demo video, to support stakeholder engagement. Enhanced project maintainability by expanding documentation scaffolding, updating the README, and adding onboarding materials. Addressed repository hygiene by cleaning up outdated notebooks and documentation, reducing confusion for future contributors. The work improved forecast reliability, streamlined onboarding, and enabled more effective communication with both technical and non-technical audiences.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
11Total
Bugs
1
Commits
11
Features
3
Lines of code
16,673
Activity Months1
Your Network
18 peopleSame Organization
@srmap.edu.in2
Work History
December 2024
11 Commits • 3 Features
Dec 1, 2024December 2024 was focused on delivering measurable business value for the FutureCart AI-Driven-Demand-Prediction project via model tuning, asset enablement, and repository hygiene. Key deliverables include a grid-search based Ridge regression hyperparameter tuning workflow for a multivariate forecast, the preparation of presentation and demo materials for stakeholder demonstrations, and ongoing documentation scaffolding with README updates. Additionally, outdated documentation and notebooks were cleaned up to reduce confusion and maintain a clean baseline for future work. These efforts collectively improved forecast reliability, enabled compelling demos for stakeholders, and strengthened maintainability and onboarding for the team.
11 Commits • 3 Features
Dec 1, 2024December 2024 was focused on delivering measurable business value for the FutureCart AI-Driven-Demand-Prediction project via model tuning, asset enablement, and repository hygiene. Key deliverables include a grid-search based Ridge regression hyperparameter tuning workflow for a multivariate forecast, the preparation of presentation and demo materials for stakeholder demonstrations, and ongoing documentation scaffolding with README updates. Additionally, outdated documentation and notebooks were cleaned up to reduce confusion and maintain a clean baseline for future work. These efforts collectively improved forecast reliability, enabled compelling demos for stakeholders, and strengthened maintainability and onboarding for the team.
December 2024
Activity
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Quality Metrics
Correctness98.2%
Maintainability98.2%
Architecture98.2%
Performance98.2%
AI Usage23.6%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
Code CleanupData ScienceData VisualizationDocumentationForecastingGrid SearchHyperparameter TuningMachine LearningMatplotlibPandasProject PlanningPythonRidge RegressionScikit-learnTechnical Writing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline