Hello Student,

A new question is now available in the Answer App (answer-morelia) regarding the iterative approach for a one-parameter predictive model. You can win 20 points for this module.

The activity is intended to reinforce the concepts discussed during the lecture, particularly:

• Prediction using a one-parameter model.
• Residual error calculation.
• Iterative parameter updating.
• The effect of the learning rate.
• The influence of noisy measurements and outliers.

Please solve the numerical exercise and, more importantly, explain the reasoning behind the iterative update process in your own words. The objective is to understand how a predictive model learns from data rather than simply applying the equations.

Best regards,

Gerardo Marx

Professor and Lecturer
https://gmarx.itmorelia.com/lectures/artificial