We are going to learn the introduction of machine learning and linear regression in R 4.0 programming. We will start with the introduction of machine learning then we will discuss the introduction of linear regression. I will also discuss types of linear regression and use cases of linear regression. there are two types of linear regression; simple linear regression and multiple linear regression. Use cases of linear regression are in house price prediction, stock price prediction, Twitter popularity prediction. I will thereafter show you how to analyze the Boston housing dataset. We will analyze dataset variables to understand the variable dependency for the linear regression model. I will show you the linear and non-linear regression models. Thereafter, I will show how you can improve the accuracy of a linear regression model.

We are going to learn the introduction of machine learning and linear regression in R 4.0 programming. We will start with the introduction of machine learning then we will discuss the introduction of linear regression. I will also discuss types of linear regression and use cases of linear regression. there are two types of linear regression; simple linear regression and multiple linear regression. Use cases of linear regression are in house price prediction, stock price prediction, Twitter popularity prediction. I will thereafter show you how to analyze the Boston housing dataset. We will analyze dataset variables to understand the variable dependency for the linear regression model. I will show you the linear and non-linear regression models. Thereafter, I will show how you can improve the accuracy of a linear regression model.

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This "Machine Learning with R Full Course With R" video by Edureka will help you to understand the core concepts of Machine Learning and tell you how you can implement popular Machine Learning algorithms using R.