End-to-End Product Sales Forecasting System using Machine Learning

1. 1Collect historical sales data using tools like SQL or pandas
2. 2Preprocess data by handling missing values and normalization
3. 3Train a machine learning model using libraries like scikit-learn or TensorFlow
4. 4Evaluate model performance using metrics like mean absolute error or mean squared error
5. 5Deploy the model using a framework like Flask or Django to generate forecasts

Data scientists and product managers can benefit from this system to inform business decisions and optimize inventory management

💡 Accurate sales forecasting is crucial in retail and can be achieved with machine learning

Boost retail sales forecasting with machine learning!