Python: E-commerce Sales Predictor

This Python snippet uses machine learning techniques with the 'scikit-learn' library to predict future sales based on historical e-commerce data. It's ideal for e-commerce platforms looking to forecast sales and manage inventory more effectively.

The snippet trains a regression model on past sales data, which can predict future trends and help businesses prepare for demand fluctuations. This predictive capability is crucial for optimizing stock levels and minimizing overstock or stockouts.

Using 'scikit-learn', the code preprocesses the data, selects features, and trains a predictive model. The integration of machine learning in sales forecasting offers a significant advantage in planning and strategy formulation.

This tool is particularly valuable for e-commerce business analysts and data scientists who need to implement advanced analytics to drive decision-making and improve operational efficiency.

Below is the complete implementation of the e-commerce sales predictor, a powerful tool for enhancing business intelligence and inventory management.