springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction
Dec 2024 – Dec 2024
1 Month active
Languages Used
Jupyter NotebookPDFPython
Technical Skills
Data AnalysisData CleaningData VisualizationFeature EngineeringInternship ProjectMatplotlib
Bharathk099
PROFILE
Bharathk099
Bharath worked on the FutureCart--AI-Driven-Demand-Prediction repository, delivering an end-to-end demand forecasting notebook and integrating core application features for e-commerce analytics. He approached the problem by loading, merging, and cleaning data, handling missing values and outliers, and engineering temporal features to support robust time series analysis. Using Python, Pandas, and Jupyter Notebook, Bharath developed data visualization workflows and ensured documentation and asset management were up to date, removing obsolete materials and packaging deliverables. The work focused on enabling data-driven decision-making and faster onboarding, demonstrating depth in data analysis, feature engineering, and project hygiene over the course of the internship.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
3
Lines of code
36,693
Activity Months1
Your Network
16 peopleWork History
December 2024
9 Commits • 3 Features
Dec 1, 2024December 2024: Delivered core analytics and product readiness for FutureCart, including an end-to-end demand forecasting notebook, application development and integration, and documentation/asset housekeeping. No critical bugs logged; focus on feature delivery and repository hygiene to enable faster onboarding and data-driven decisions. Technologies demonstrated included Python, Jupyter notebooks, Pandas, data visualization, feature engineering, and documentation tooling.
9 Commits • 3 Features
Dec 1, 2024December 2024: Delivered core analytics and product readiness for FutureCart, including an end-to-end demand forecasting notebook, application development and integration, and documentation/asset housekeeping. No critical bugs logged; focus on feature delivery and repository hygiene to enable faster onboarding and data-driven decisions. Technologies demonstrated included Python, Jupyter notebooks, Pandas, data visualization, feature engineering, and documentation tooling.
December 2024
Activity
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Quality Metrics
Correctness82.2%
Maintainability82.2%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPDFPython
Technical Skills
Data AnalysisData CleaningData VisualizationFeature EngineeringInternship ProjectMatplotlibPandasSeabornStatsmodelsTime Series Analysis
Repositories Contributed To
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