first of all, pardon me if I’m making any mistakes with the tags and that, I’m new, so i don’t know if I’m doing it right
my doubt is quite simple, in the deep learning courses when you have an assigned task, should i just focus on what I’m asked to do(and optional things), and learn it right, or its required to know how all the entire code works, including the pre done cells and parts of the code, i have my doubts on which one would be a lot more effective and how its intended
The intention here is to know how to solve the part that is ask you to solve! That is the crucial part.
But it’s good to read and understand the other parts/cells, too; if you can reproduce them, it’s even better!
Hello,
The most important thing is learning the topic of course. I did not give too much efford to understand each line of code because there are a lot of ways to do that. After I had finished this course, I started to continue my research in Pytorch, Keras, Numpy, Ultralytics etc. (What I want to learn.)
You should learn what is it, before learn how you can do it.
I would do the activity and just run through the notebooks how they set them up, Once you understand whats going on, then I would try it out locally on your PC or VM
It’s usually best to focus on understanding the main tasks and concepts first. Once you feel comfortable, you can explore the entire code to see how everything fits together. Balancing both approaches will help you learn effectively.