The branch bostonhousing_dataset is an example of linear regression for a dataset with independent variables and a dependent feature related to property values. The example demonstrates the process of generating a correlation matrix based on data from the .xlsx file. The correlation matrix is generated using the matplotlib library for consecutive features, enabling observation of the characteristic feature of correlation convergence (displayed on a graph as a straight line).
The process of generating linear regression consists of loading data from a file, dividing the data into scientific and test batch, and training the model.
To run the project, use the Google Colab environment via the Gist website (add learning data from the github project resources): gist link
Or you can download repository branch and launch the project locally using DataSpell or PyCharm by JetBrains. You can also launch it using Spyder IDE. When launching locally remember to have the dataset files inside your project directory to avoid problems.