springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction
Dec 2024 – Jan 2025
2 Months active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
AIARIMAData AnalysisData ScienceData VisualizationDocumentation
CHRIS_JOY
PROFILE
Chris_joy
Worked on the FutureCart--AI-Driven-Demand-Prediction repository, building a foundation for AI-driven demand forecasting through Jupyter Notebooks and Python. Established a reproducible workflow by consolidating assets, removing obsolete or duplicate files, and updating documentation to streamline onboarding and experimentation. Applied data science and machine learning techniques, including ARIMA and time series forecasting, to enable robust model prototyping and reliable demand predictions. Focused on repository hygiene and asset management, ensuring that experimentation cycles remained efficient and insights were dependable. Emphasized technical writing and documentation to support collaboration, while leveraging tools like Optuna for hyperparameter tuning and data visualization throughout the project.
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
25Total
Bugs
2
Commits
25
Features
5
Lines of code
28,316
Activity Months2
Your Network
16 peopleWork History
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly performance summary for the repository springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction. Focused on asset management for the AI-driven demand forecasting workflow. Delivered a new Jupyter Notebook to advance experimentation and predictions, and removed an obsolete notebook to ensure asset currency and reduce confusion. These changes improve reproducibility, accelerate experimentation cycles, and strengthen the reliability of insights used for demand planning.
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly performance summary for the repository springboardmentor436z/FutureCart--AI-Driven-Demand-Prediction. Focused on asset management for the AI-driven demand forecasting workflow. Delivered a new Jupyter Notebook to advance experimentation and predictions, and removed an obsolete notebook to ensure asset currency and reduce confusion. These changes improve reproducibility, accelerate experimentation cycles, and strengthen the reliability of insights used for demand planning.
January 2025
December 2024
23 Commits • 4 Features
Dec 1, 2024December 2024 monthly summary for the FutureCart AI-Driven-Demand-Prediction project. Focused on establishing a stable asset and notebook foundation, improving repository hygiene, and documenting the project for faster onboarding and reliable experimentation.
December 2024
23 Commits • 4 Features
Dec 1, 2024December 2024 monthly summary for the FutureCart AI-Driven-Demand-Prediction project. Focused on establishing a stable asset and notebook foundation, improving repository hygiene, and documenting the project for faster onboarding and reliable experimentation.
Activity
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Quality Metrics
Correctness89.6%
Maintainability89.6%
Architecture89.6%
Performance89.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
AIARIMAData AnalysisData ScienceData VisualizationDocumentationHyperparameter TuningMachine LearningOptunaPythonRepository ManagementTechnical WritingTime Series AnalysisTime Series Forecasting
Repositories Contributed To
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