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MATLAB: Data Regression with MATLAB
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Advanced Provider : Gabriel Popoola 3 Lessons · 17m in Arabic, German, English, Spanish, French, Portuguese, Chinese
Course Description
Data regression models are the foundation of various systems in defense and industry. Regression is the process of mapping a set of inputs to a continuous output variable or, in the case of multiple regression, multiple continuous variables when looking at regression. There are a large number of factors that can contribute to an increase or decrease in model performance and reliability. Before diving into the training and selection of your regression model, it is essential that you have an excellent foundational understanding of just what regression is as well as the workflow associated with selecting the best model for your application and needs. In this MATLAB module, you will learn about data regression and how to implement it in MATLAB.
After completing this module, you will be able to apply what you learned to any project or task involving data regression. This will enable you to create and implement different predictive models. These can be used in applications for things such as finance, advertising, weather/climate, and even medicine.
What You'll Learn
- Define what regression is and how it maps a set of inputs to a continuous output variable
- Recognize the concepts of inputs and outputs in data regression, including multiple regression with multiple continuous variables
- Understand the data regression model workflow
- Select the best regression model for your application and needs
- Implement data regression in MATLAB to create and apply predictive models
Key Takeaways
- Data regression models are the foundation of various systems in defense and industry.
- Regression is the process of mapping a set of inputs to a continuous output variable, or, in multiple regression, to multiple continuous variables.
- A large number of factors can contribute to an increase or decrease in model performance and reliability.
- A strong foundational understanding of regression and its model-selection workflow is essential before training and selecting a regression model.
- Regression-based predictive models can be used in applications such as finance, advertising, weather/climate, and medicine.
Frequently Asked Questions
What will I learn in this MATLAB module?
You will learn about data regression and how to implement it in MATLAB, including defining what regression is, recognizing the concepts of inputs and outputs, and understanding the regression model workflow.
What topics does this course cover?
The course covers a regression overview, regression model selection, and the data regression model workflow.
What can I do after completing this module?
After completing this module, you will be able to apply what you learned to any project or task involving data regression, enabling you to create and implement different predictive models.
Where can the predictive models from this course be applied?
These predictive models can be used in applications such as finance, advertising, weather/climate, and even medicine.
What skills does this course develop?
This course develops skills in Linear Regression, MATLAB, Nonlinear Regression, Ordinary Least Squares (Regression Analysis), Regression Analysis, and Simple Linear Regression.
