Developed a machine learning–driven desktop application using TensorFlow, scikit-learn, and PyQt5 to predict Projected and Actual invoices based on business and location data. The system preprocesses structured inputs (numeric + categorical), trains a neural network for regression, and provides users with an intuitive interface featuring dynamic dropdowns, input validation, and real-time predictions.