diff --git a/doc/src/week35/week35.do.txt b/doc/src/week35/week35.do.txt
index de59a0647..69b4b2b0f 100644
--- a/doc/src/week35/week35.do.txt
+++ b/doc/src/week35/week35.do.txt
@@ -13,12 +13,17 @@ DATE: today
 !split
 ===== Thursday August 27 =====
 
-"Video of Lecture":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureAug27.mp4?vrtx=view-as-webpage".
-
+The main topics on Thursday are:
+o Repetition from last week on linear regression
+o Discussion of how to prepare data and examples of applications of linear regression
+o Mathematical interpretations of Linear Regression
+o Start discussing Ridge regression and Singular Value Decomposition
 
 !split
 ===== Why Linear Regression (aka Ordinary Least Squares and family), repeat from last week =====
 
+We need first a reminder from last week about linear regression. 
+
 Fitting a continuous function with linear parameterization in terms of the parameters  $\bm{\beta}$.
 * Method of choice for fitting a continuous function!
 * Gives an excellent introduction to central Machine Learning features with _understandable pedagogical_ links to other methods like _Neural Networks_, _Support Vector Machines_ etc