1 00:00:01,990 --> 00:00:08,600 This session is about understanding the concept of the mental independent variables. 2 00:00:09,250 --> 00:00:10,750 This is a very important concept. 3 00:00:11,500 --> 00:00:13,900 Now, let's see this with an example. 4 00:00:16,220 --> 00:00:21,590 The height to which the plant grows is dependent on. 5 00:00:22,740 --> 00:00:31,700 The amount of water that is used and the quantity of fertilizers, there are other factors like the 6 00:00:31,710 --> 00:00:36,750 day on which the seeds were planted, whether so many factors. 7 00:00:37,530 --> 00:00:42,390 But let's just look at the factors behind the plant rules. 8 00:00:42,810 --> 00:00:53,000 And the two factors we are analyzing are what you see behind OK as a factor, as if it is. 9 00:00:53,280 --> 00:00:57,030 And fertilizer and what? 10 00:00:58,200 --> 00:01:03,510 OK, so the growth of the combine is dependent on these two. 11 00:01:04,590 --> 00:01:15,170 Why fertilizers of the Department of Energy, something of which we are not concerned as of now, and 12 00:01:15,450 --> 00:01:21,150 so we are considering acres and acres of land is dependent on fertilizers and what? 13 00:01:24,620 --> 00:01:26,090 So in this case. 14 00:01:27,030 --> 00:01:33,210 Quantity of fertilizers and quantity of water are independent variables, and the height of the plant 15 00:01:33,480 --> 00:01:35,070 is dependent variable. 16 00:01:35,910 --> 00:01:37,320 Do you understand this concept? 17 00:01:37,980 --> 00:01:44,100 You have to establish this dependent and independent variables at the start of your machine learning 18 00:01:44,100 --> 00:01:45,220 or deep learning project. 19 00:01:45,480 --> 00:01:48,930 So there's a very, very important concept right now. 20 00:01:48,940 --> 00:01:51,200 Let's see some examples from Real World. 21 00:01:51,960 --> 00:01:59,310 The insurance company is trying to ascertain how much they should charge the customer for insurance. 22 00:01:59,310 --> 00:01:59,680 Right. 23 00:01:59,970 --> 00:02:04,440 So the factors they will consider are age six, BMI. 24 00:02:04,470 --> 00:02:12,630 BMI is body mass index number of children the person has got, whether he's a smoker or not, which 25 00:02:12,630 --> 00:02:14,020 region he or she comes from. 26 00:02:14,180 --> 00:02:14,530 Right. 27 00:02:14,910 --> 00:02:22,870 So all these are independent variables and insurance charges is my dependent variable. 28 00:02:22,890 --> 00:02:30,170 That means quantum of insurance charges is dependent on these factors. 29 00:02:31,590 --> 00:02:35,270 Are you getting it are dependent on these factors? 30 00:02:36,390 --> 00:02:39,720 Now, let's see one more example from the world of banking. 31 00:02:40,440 --> 00:02:44,260 The bank is trying to ascertain whether loans should be granted or not. 32 00:02:44,740 --> 00:02:51,510 OK, and what are the factors the bank is taking into account gender, whether that individual is married 33 00:02:51,510 --> 00:02:58,140 or not, number of dependents, education, whether that individual is self-employed or working for 34 00:02:58,140 --> 00:02:59,090 an organization. 35 00:02:59,460 --> 00:03:00,930 What is applicant's income? 36 00:03:02,290 --> 00:03:04,100 Is that a Koplik and income? 37 00:03:04,540 --> 00:03:09,130 What is the loan amount loan to your credit history and property area? 38 00:03:09,140 --> 00:03:11,710 If you see there are 11 factors, right? 39 00:03:12,010 --> 00:03:16,120 And all these factors are independent variables. 40 00:03:17,190 --> 00:03:25,170 And why should Lorne be granted or not is a dependent variable because should Lorne be granted or not, 41 00:03:25,170 --> 00:03:28,220 is dependent on all these factors, right? 42 00:03:28,350 --> 00:03:33,660 It is like why is a function of X one, X two and so on and so forth. 43 00:03:34,840 --> 00:03:42,400 Right, I hope you're all clear about the concept of dependent on independent variables. 44 00:03:43,090 --> 00:03:43,540 OK.