Read a detalied article on my blog.
- Client: US Grocery store chain with IoT sensors, facing perishable supply chain challenges.
- Challenge: Optimize supply chain for perishable items.
- Request: Use data and AI for efficient supply chain management.
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EDA on Client Data:
- Analyzed client data using Google Colab.
- Utilized pandas and seaborn for EDA.
- Requested additional data.
- Jupyter Notebook.
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Data Modeling:
- Tasked with predicting product stock levels using sales and sensor data.
- Developed a strategic plan.
- Action Plan PowerPoint.
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Model Building and Interpretation:
- Combined, transformed, and modeled 3 datasets.
- Created a Python workflow for EDA, model testing, and finetuning.
- Jupyter Notebook.
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Machine Learning Production:
- Developed a Python module adhering to PEP 8.
- Created functions for data loading and model evaluation.
- Python Module.