Description

Utilizing the PyTorch framework, a sophisticated deep learning model has been trained for accurate house price prediction. This model, designed for regression tasks, leverages powerful neural network architectures. By comprehensively analyzing various features such as lot area, building type, neighborhood, and more, the model establishes intricate relationships between inputs and target prices. Through rigorous training on a large dataset, it learns to capture both linear and nonlinear correlations, enabling precise predictions. This PyTorch-based house price prediction solution offers a robust tool for real estate valuation and decision-making.