With this thread, I would like to discuss what are the main steps typically followed to address a ML project. The discussion is loosely based on Chapter 2 of the textbook. However, of course, the point is not to copy and paste passages from the book. Rather, we want to come up with a broad overview of how to approach a full project. To guide a little bit the discussion, I will be posting different questions during the week.
In order to grant the possibility to participate to all the students, we enforce the following rule:
2-max: Each student can post a maximum of two consecutive comments. After that, the student will have to wait for at least two more students to post comments before being able to post again comments. The same rule applies at every iteration.
4-total: As per IE rules, each student can post a maximum of 4 posts per week.
Let us open the thread with the following question:
Q1: The first step of a ML project is to “look at the big picture”. What does this entail? What are some of the facts we might want to collect or decide upon before starting with the project?
