So in this lecture, I'm going to tell you where to get the exercises for this cause.
This is aside from any exercises already mentioned in the lectures in order to get these exercises.
Simply go to deep learning courses dot com and look for a course called PyTorch Deep Learning and Artificial
Intelligence Exercise Pack.
Note that this is free and there is an exercise with an associated data set for every section of this
course.
So you get to practice every algorithm you learned, so you'll have one exercise for linear regression,
one exercise for logistic regression, one exercise for an ends and so forth.
Now you might be wondering why does it say PyTorch?
What if I'm in your TensorFlow course?
Recall that this doesn't matter because the topics in deep learning don't change.
It doesn't matter if you're using TensorFlow PyTorch jacks or anything else, the same deep learning
topics would be taught.
Therefore, there is just one set of exercises which can be used for all students of these courses.
Now, there's one important idea that I want to share with you before you attempt these exercises.
You see people often ask, why don't you make a lecture showing us your solution to the exercise?
At this point, you have to keep in mind the rule.
All data is the same.
What this means is that you've already been given the solution to these exercises.
The code is exactly the same as what you saw in this course.
The only thing that's going to change is the data set.
Therefore, there's technically nothing stopping you from simply taking the code from this course and
changing the part where we load in the data file.
Now, obviously, you probably don't want to do that, since it won't help you practice.
But I want to make it clear what we mean by all data is the same.
This means that even when you change the data set, you don't have to change the code because the code
doesn't care what your data is from the eyes of the algorithm.
All data looks exactly alike.
Now, there's another important point I want to make here, and this is that for those of you looking
for exercises and not knowing what to do without these exercises, this is definitely an opportunity
for some self introspection.
In particular, I'm going to tell you why this is a silly question, and hopefully you'll agree.
You see, the reason you are taking this course is not just that you want to learn deep learning and
not just that you want to learn PyTorch.
You, of course, have some reason you want to learn these things.
For example, you want to classify images of brain abnormalities or you want to get a job in computer
vision.
Once you tap into this reason, you have exactly what you need to exercise what you've learned.
At this point, you can simply apply these techniques to data sets from your actual life in the real
world.
Now, if you think you don't yet have such a reason and you're perhaps just learning this topic for
enjoyment, this still applies even though I've given you some data sets to work with in these exercises.
They might not be what you are most interested in working with.
I simply don't believe that there are students in this course.
You don't have some idea of what they want to do with what they've learned.
And as such, exercises are not so much me telling you what data sets it work with, but you asking
yourself what you would like to do.
In fact, that itself should be an exercise.
So consider it as such.
Think about why are you here?
How are you going to apply what you've learned?
And once you have your answer, simply do what you've decided you want to do.