1
00:00:11,080 --> 00:00:15,640
So in this lecture, I'm going to tell you where to get the exercises for this cause.

2
00:00:16,330 --> 00:00:22,690
This is aside from any exercises already mentioned in the lectures in order to get these exercises.

3
00:00:22,720 --> 00:00:29,260
Simply go to deep learning courses dot com and look for a course called PyTorch Deep Learning and Artificial

4
00:00:29,260 --> 00:00:31,570
Intelligence Exercise Pack.

5
00:00:32,290 --> 00:00:37,930
Note that this is free and there is an exercise with an associated data set for every section of this

6
00:00:37,930 --> 00:00:38,470
course.

7
00:00:38,890 --> 00:00:44,620
So you get to practice every algorithm you learned, so you'll have one exercise for linear regression,

8
00:00:44,980 --> 00:00:49,330
one exercise for logistic regression, one exercise for an ends and so forth.

9
00:00:50,920 --> 00:00:53,740
Now you might be wondering why does it say PyTorch?

10
00:00:54,100 --> 00:00:55,900
What if I'm in your TensorFlow course?

11
00:00:56,500 --> 00:01:00,970
Recall that this doesn't matter because the topics in deep learning don't change.

12
00:01:01,450 --> 00:01:07,180
It doesn't matter if you're using TensorFlow PyTorch jacks or anything else, the same deep learning

13
00:01:07,180 --> 00:01:08,440
topics would be taught.

14
00:01:09,040 --> 00:01:14,620
Therefore, there is just one set of exercises which can be used for all students of these courses.

15
00:01:19,260 --> 00:01:24,210
Now, there's one important idea that I want to share with you before you attempt these exercises.

16
00:01:24,840 --> 00:01:30,280
You see people often ask, why don't you make a lecture showing us your solution to the exercise?

17
00:01:30,960 --> 00:01:33,170
At this point, you have to keep in mind the rule.

18
00:01:33,180 --> 00:01:34,620
All data is the same.

19
00:01:35,280 --> 00:01:39,750
What this means is that you've already been given the solution to these exercises.

20
00:01:40,260 --> 00:01:44,120
The code is exactly the same as what you saw in this course.

21
00:01:44,610 --> 00:01:47,250
The only thing that's going to change is the data set.

22
00:01:47,880 --> 00:01:53,160
Therefore, there's technically nothing stopping you from simply taking the code from this course and

23
00:01:53,160 --> 00:01:55,410
changing the part where we load in the data file.

24
00:01:56,040 --> 00:02:00,480
Now, obviously, you probably don't want to do that, since it won't help you practice.

25
00:02:01,020 --> 00:02:04,680
But I want to make it clear what we mean by all data is the same.

26
00:02:05,460 --> 00:02:10,980
This means that even when you change the data set, you don't have to change the code because the code

27
00:02:11,040 --> 00:02:15,010
doesn't care what your data is from the eyes of the algorithm.

28
00:02:15,030 --> 00:02:17,030
All data looks exactly alike.

29
00:02:21,690 --> 00:02:26,520
Now, there's another important point I want to make here, and this is that for those of you looking

30
00:02:26,520 --> 00:02:32,700
for exercises and not knowing what to do without these exercises, this is definitely an opportunity

31
00:02:32,700 --> 00:02:34,530
for some self introspection.

32
00:02:35,190 --> 00:02:40,050
In particular, I'm going to tell you why this is a silly question, and hopefully you'll agree.

33
00:02:40,860 --> 00:02:45,600
You see, the reason you are taking this course is not just that you want to learn deep learning and

34
00:02:45,600 --> 00:02:47,550
not just that you want to learn PyTorch.

35
00:02:48,120 --> 00:02:51,210
You, of course, have some reason you want to learn these things.

36
00:02:51,780 --> 00:02:57,690
For example, you want to classify images of brain abnormalities or you want to get a job in computer

37
00:02:57,690 --> 00:02:58,200
vision.

38
00:02:59,220 --> 00:03:04,770
Once you tap into this reason, you have exactly what you need to exercise what you've learned.

39
00:03:05,400 --> 00:03:11,580
At this point, you can simply apply these techniques to data sets from your actual life in the real

40
00:03:11,580 --> 00:03:12,120
world.

41
00:03:12,870 --> 00:03:17,400
Now, if you think you don't yet have such a reason and you're perhaps just learning this topic for

42
00:03:17,400 --> 00:03:23,940
enjoyment, this still applies even though I've given you some data sets to work with in these exercises.

43
00:03:24,300 --> 00:03:27,210
They might not be what you are most interested in working with.

44
00:03:27,810 --> 00:03:30,450
I simply don't believe that there are students in this course.

45
00:03:30,750 --> 00:03:34,560
You don't have some idea of what they want to do with what they've learned.

46
00:03:35,190 --> 00:03:41,280
And as such, exercises are not so much me telling you what data sets it work with, but you asking

47
00:03:41,280 --> 00:03:43,470
yourself what you would like to do.

48
00:03:44,310 --> 00:03:46,920
In fact, that itself should be an exercise.

49
00:03:47,190 --> 00:03:48,810
So consider it as such.

50
00:03:49,440 --> 00:03:51,150
Think about why are you here?

51
00:03:51,510 --> 00:03:53,790
How are you going to apply what you've learned?

52
00:03:54,390 --> 00:03:58,470
And once you have your answer, simply do what you've decided you want to do.