beckyydo/retail-machine-learning

Using Python, Javascript, Postgres and HTML built a retail dashboard containing interactive visualization and forecast generated by Facebook Prophet and other machine learning models. Grocery recommendation system uses k-means clustering and the surprise algorithm

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Emerging

This retail dashboard helps store managers and business analysts understand their sales performance, predict future trends, and personalize customer experiences. It takes historical sales data, customer purchase records, and stock information to generate interactive visualizations, sales forecasts, and tailored grocery recommendations for individual shoppers. The tool assists retail professionals in making data-driven decisions for inventory, marketing, and customer engagement.

No commits in the last 6 months.

Use this if you are a retail manager or analyst needing to forecast sales, predict stock prices, and provide personalized product recommendations to customers.

Not ideal if you need to perform deep, custom statistical analysis beyond the provided visualizations and model outputs, or if your primary need is real-time operational reporting.

retail-management sales-forecasting customer-recommendations inventory-planning market-basket-analysis
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 18 / 25

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12

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Jupyter Notebook

License

Last pushed

Jun 14, 2021

Commits (30d)

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