Curve Fitting Onramp

Learn the basics of curve fitting with the Curve Fitter app. You will learn about what makes a fit the best, how to compare multiple fits, and postprocess fit results to determine the most efficient driving speed for an electric vehicle.

Course modules

Introduction

Familiarize yourself with numerical optimization and the course.

Lessons:
  • Course Overview
  • Fit Data Interactively

Find a Best Fit

Fit a Polynomial to data in the Curve Fitter App.

Lessons:
  • What is a Best Fit
  • Find a Best Fit

Statistical Comparisons of Multiple Fits

Fit a variety of models to data and choose the best model.

Lessons:
  • Compare Multiple Fits
  • Measures of Goodness of Fit
  • Avoid Overfitting
  • Model Selection

Fit a Custom Model

Fit a custom model of an electric vehicle to the range data.

Lessons:
  • Build a Custom Model
  • Call a Custom EV Model
  • Use a Custom Model in Curve Fitter

Postprocess Fit Results

Work with fit results.

Lessons:
  • Fit Postprocessing Functions
  • Analyze Many Datasets with Generated Code

Conclusion

Learn next steps and give feedback on the course.

Lessons:
  • Additional Resources
  • Survey

Optimization Onramp

Learn the basics of solving optimization problems in MATLAB using the problem-based approach.

Statistics Onramp

Get started using statistical methods for analysis in MATLAB.

Machine Learning Onramp

Learn the basics of practical machine learning methods for classification problems.

MATLAB Onramp

Get started quickly with the basics of MATLAB.