Sales Forecasting Using Time Series Data

Data preprocessing to clean the dataset.
Feature engineering to create time-series features (e.g., lag values, rolling means).
Machine learning model training using XGBoost to forecast future sales.
Evaluation of the model with metrics like Mean Absolute Error (MAE).
Visualization of actual vs. predicted sales.

Dataset

The dataset is obtained from the UCI Machine Learning Repository. It contains retail transaction data from a UK-based online store.