Hello everyone!
In this notebook we start using ML algorithms to analyse a usual dataset. We are going to use Linear Regression method for create a model on dataset and then evaluate the results!
In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.
If we have x feature for predicting y (target variable) linear regressions generate a Two-dimensional line equation and if we have n (more than 2) variables linear regressions generate a n-dimenshional line equation like this:
We use Real Estate dataset to make a model that predict house prices based on 6 features. In the following, You can realize more about dataset.