Unified Fitting and Modeling in Wolfram Language

The new unified model framework brings together statistical modeling, machine learning and symbolic computation in a single, consistent interface. We show how diverse model families—linear, nonlinear, generalized additive, tree-based and more—fit into the same symbolic pipeline. Built for efficiency with the new Tabular object, the framework supports high-performance fitting on large datasets while preserving Wolfram Language's advantages in probability, integration and symbolic analysis.