springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction
Dec 2024 – Dec 2024
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data PreprocessingFeature EngineeringFile ManagementForecastingMatplotlibModel Evaluation
Uppunuthala Abhilash
PROFILE
Uppunuthala Abhilash
Developed a data-driven forecasting capability for the FutureCart--AI-Driven-Demand-Prediction repository, focusing on inventory planning and asset organization. Leveraging Python and Jupyter Notebook, the work centered on implementing SARIMAX-based time series forecasting for demand and quantity, incorporating exogenous variables, hyperparameter tuning, and comprehensive model evaluation using metrics such as MAE, RMSE, MAPE, and R-squared. The project also included detailed visualizations with Matplotlib and robust data preprocessing using Pandas. Asset management was improved through systematic file organization, renaming, and cleanup, while documentation was refined to ensure accurate branding, aligning technical deliverables with broader business and product objectives.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
15Total
Bugs
0
Commits
15
Features
3
Lines of code
60,052
Activity Months1
Your Network
16 peopleWork History
December 2024
15 Commits • 3 Features
Dec 1, 2024December 2024 monthly summary for springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction. This period delivered a data-driven forecasting capability for inventory planning, improved asset governance, and branding accuracy across the project. The work emphasizes business value through accurate demand signals, organized assets, and clear documentation, aligning technical effort with product goals.
15 Commits • 3 Features
Dec 1, 2024December 2024 monthly summary for springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction. This period delivered a data-driven forecasting capability for inventory planning, improved asset governance, and branding accuracy across the project. The work emphasizes business value through accurate demand signals, organized assets, and clear documentation, aligning technical effort with product goals.
December 2024
Activity
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Quality Metrics
Correctness97.4%
Maintainability97.4%
Architecture97.4%
Performance97.4%
AI Usage25.4%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data PreprocessingFeature EngineeringFile ManagementForecastingMatplotlibModel EvaluationPandasSARIMAXScikit-learnTime Series Analysis
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