Sales Forecasting

<p><strong>Sales forecasting</strong> plays a crucial role in the retail industry, helping businesses predict future sales, optimize inventory management, and improve decision-making. Retailers face <strong>challenges </strong>in accurately predicting demand due to <strong>various factors </strong>such as seasonality, promotions, and external economic conditions. Machine learning techniques can help provide more accurate forecasts by <strong>learning from historical </strong>sales data and identifying <strong>patterns</strong>.</p><p></p><p>This workflow will demonstrate the use of machine learning (i.e <strong>ARIMA</strong>, <strong>SARIMA</strong>), specifically time series forecasting methods, to predict sales. This lab activity includes:</p><ul><li><p>Preprocess historical sales data.</p></li><li><p>Data Analysis on time series data</p></li><li><p>Train a forecasting model.</p></li><li><p>Evaluate the model's performance.</p></li><li><p>Generate future sales predictions.</p></li></ul>