It is a synthetic financial transaction log designed specifically for training and testing supervised Machine Learning models, such as text classifiers or expense trackers.
Dataset Overview
Size: 1,000 unique transaction rows.
Nature: Synthetic (generated via Python) to ensure privacy while maintaining realistic patterns.
Primary Use Case: Multi-class Classification (Predicting the category based on the description).
