## Math, Statistics,and Optimization

**Classification Learner**

Train models to classify data using supervised machine learning

**Curve Fitting**

Fit curves and surfaces to data

**Distribution Fitting**

Fit probability distributions to data

**MBC Model Fitting**

Create experimental designs and statistical models for model-based calibration

**MBC Optimization**

Generate optimal lookup tables for model-based calibration

**MuPAD Notebook**

Perform and document symbolic calculations

**Neural Net Clustering**

Solve clustering problem using self-organizing map (SOM) networks

**Neural Net Fitting**

Solve fitting problem using two-layer feed-forward networks

**Neural Net Pattern Recognition**

Solve pattern recognition problem using two-layer feed-forward networks

**Neural Net Time Series**

Solve nonlinear time series problem using dynamic neural networks

**Optimization**

Set up and solve optimization problems

**PDE**

Solve partial differential equations on 2-D regions