pass schedule

Author: QB3

src/content/lessons/introduction.mdx

@@ -12,10 +12,7 @@ import TypicalGallery from '../../components/TypicalGallery.astro'
 
 ### Introduction
 
-This is an introduction to the main settings encountered in generative modelling. The first Lectures will introduce the main algorithms and concept for the vanilla unconditional generative modelling task.
-At the end of the course, we will make excursions to class-conditional and text-conditional generative modelling.
-
-The goal of this Lecture is to understand the relationship between vanilla unconditional generative modelling and industrial generative models such as DALL-E, Stable Diffusion, GPT, etc.
+This is an introduction to the main settings encountered in generative modelling: the goal of this Lecture is to understand the relationship between vanilla unconditional generative modelling and industrial generative models such as DALL-E, Stable Diffusion, GPT, etc.
 
 
 #### Unconditional Generative Modelling
@@ -207,7 +204,6 @@ More precisely, given a text description $y^{new}$ we want to be able to generat
 
 #### 1 and 2-Dimensional Examples
 
-#### Maximum Likelihood
 
 ### References
 - https://people.cs.umass.edu/~domke/courses/sml/10probabilistic.pdf