Explore the new unified model framework in Wolfram Language that seamlessly integrates statistical modeling, machine learning, and symbolic computation through a single, consistent interface. Discover how diverse model families including linear, nonlinear, generalized additive, and tree-based models operate within the same symbolic pipeline. Learn about the framework's efficiency optimizations using the new Tabular object, which enables high-performance fitting on large datasets while maintaining Wolfram Language's powerful capabilities in probability, integration, and symbolic analysis. Understand how this unified approach streamlines the modeling workflow by providing consistent syntax and functionality across different model types, making it easier to compare, combine, and transition between various modeling approaches within the Wolfram ecosystem.