# How I Built a Retail Demand Forecasting App with Python and Streamlit
📰 Dev.to · Okparaji Wisdom
Learn how to build a retail demand forecasting app using Python and Streamlit to predict sales and reduce losses
Action Steps
- Build a dataset of historical sales data using Python
- Configure a Streamlit app to visualize sales trends
- Apply machine learning algorithms to forecast demand
- Test the forecasting model using metrics such as MAE and RMSE
- Deploy the app to a cloud platform for real-time forecasting
Who Needs to Know This
Data scientists and retail business analysts can benefit from this tutorial to improve demand forecasting and decision-making
Key Insight
💡 Using Python and Streamlit, retailers can build a demand forecasting app to predict sales and make data-driven decisions
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📊 Build a retail demand forecasting app with Python and Streamlit to predict sales and reduce losses 💸
Key Takeaways
Learn how to build a retail demand forecasting app using Python and Streamlit to predict sales and reduce losses
Full Article
By Okparaji Wisdom | Data Scientist | Nigeria Retailers in Nigeria lose millions of naira every...
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