Update L21

content/lectures/21/index.md

@@ -6,12 +6,14 @@ Predictive modeling
 <b>Date:</b> Dec 3, 2024
 </p>
 
-!!! danger "DRAFT"
-
-    This page is a work in progress and is subject to change at any moment.
-
 ## Learning objectives
 
-What you should be able to do after today's lecture:
+After today, you should have a better understanding of:
 
-1.  TODO:
+1.  Define linear regression, its limitations, and objective function.
+2.  Describe the purpose of loss functions in regression.
+3.  Understand the conversion of data from a DataFrame to NumPy arrays.
+4.  Develop hands-on programming skills for implementing regression in Python.
+5.  Interpret the coefficients obtained through optimization and evaluate the model's performance.
+6.  Visualize linear regression models and their fit to data.
+7.  Discuss practical considerations for model interpretation, assumptions, and limitations.