Video Description

In this video, I demonstrate how to fit a multiple linear regression model using the LASSO method in scikit-learn. I used Google Colab to create a Python notebook and run all the code. Here you have links to the Python notebook and the data file I used in the video: Notebook: https://drive.google.com/file/d/1ZeQHsvdntUbIuXz1K56zSXiBKbQ6Gmxu/view?usp=sharing Data file: https://drive.google.com/file/d/136fAH_Jy7_y_pBakhiaNx0LMoAVckhfO/view?usp=sharing In this video, you will learn how to: Follow the standard steps recommended when fitting a machine learning model. Experiment with different regularization strengths in LASSO and select the best option using cross-validation. Extract regression coefficients from the LASSO solution to assess the importance of each feature. Evaluate the prediction error of the LASSO solution in the context of the problem under investigation.