Feature Engineering and LASSO for Forecasting Models with Matlab - Machine Learning for Engineers

This video is part of the "Artificial Intelligence and Machine Learning for Engineers" course offered at the University of California, Los Angeles (UCLA). This course introduces ML/AI theory and applications that are relevant to engineering, with a focus on practical machine learning for civil engineering. This tutorial illustrates how to use Matlab to conduct feature engineering, feature normalization, feature selection, and regularization with LASSO. We then use this model to forecast the future population of India.

[@yakuparslan5542]

Hey thank you for this wonderful explanation. I'm a student and currently working on a project. I have the monthly sales liter data of a cold drink company for almost 84 months. And I have the other parameters that affects those sales such as competitor prices, air temperature, monthly precipitation etc. I have almost 8 different independent variable that affects the sales. Are those can be counted as features right away or should I manipulate every one of them like you did to create proper features. How should I proceed to forecast next months sales?

[@nikhilpatil42]

Hi.. Is there any tutorial available for multi variable input and decide the weights of each factor on the output?

[@kianamahoori9164]

I have the same question....

[@engr_yapao]

how do you compute for the accuracy of the model if you want to compare the predicted values to the actual values?