1 00:00:08,000 --> 00:00:08,000 Okay. 2 00:00:09,000 --> 00:00:19,000 So they discussed how to find out the rank of a given matrix for that purpose as they create a matrix. 3 00:00:20,000 --> 00:00:26,000 So I'm just going to the data containers here. 4 00:00:26,000 --> 00:00:29,000 I have a guess. 5 00:00:29,000 --> 00:00:30,000 Okay. 6 00:00:30,000 --> 00:00:33,000 Then create a matrix using this mosquito. 7 00:00:34,000 --> 00:00:36,000 Or like this. 8 00:00:37,000 --> 00:00:37,000 Or here. 9 00:00:37,000 --> 00:00:37,000 This is. 10 00:00:38,000 --> 00:00:39,000 I'm just increase the order. 11 00:00:40,000 --> 00:00:44,000 And right now, I'm just taking these additions. 12 00:00:44,000 --> 00:00:45,000 All right. 13 00:00:45,000 --> 00:00:49,000 Now, this is if people see any or their doesn't. 14 00:00:50,000 --> 00:00:52,000 You can just use. 15 00:00:53,000 --> 00:00:54,000 But dysfunctional. 16 00:00:55,000 --> 00:00:57,000 So those are the metrics. 17 00:00:58,000 --> 00:01:04,000 So right now I'm just deleting this function or here this is my legacy. 18 00:01:06,000 --> 00:01:06,000 The values are. 19 00:01:20,000 --> 00:01:20,000 Sexy. 20 00:01:23,000 --> 00:01:23,000 This is my. 21 00:01:24,000 --> 00:01:28,000 So my picks of three eight order. 22 00:01:29,000 --> 00:01:31,000 Now I want to find out. 23 00:01:31,000 --> 00:01:38,000 So frankly, even metrics using my pick function. 24 00:01:38,000 --> 00:01:46,000 So I just go to the long window over here and the matrix mathematics function. 25 00:01:47,000 --> 00:01:48,000 It's linear algebra. 26 00:01:49,000 --> 00:01:51,000 You can find out the metrics, right? 27 00:01:52,000 --> 00:02:01,000 So just drag and drop this function practice or here it will provide you the rank of this given real 28 00:02:01,000 --> 00:02:02,000 metrics. 29 00:02:02,000 --> 00:02:06,000 So I just increase the size 30 00:02:09,000 --> 00:02:14,000 or here is 36 and this you can find on the right. 31 00:02:15,000 --> 00:02:17,000 So I guess it on right now. 32 00:02:18,000 --> 00:02:29,000 And you see the rank is three and if I put value or here zero, then you know how just check the rank 33 00:02:30,000 --> 00:02:32,000 and you see the rank is. 34 00:02:33,000 --> 00:02:35,000 So like just continuously. 35 00:02:36,000 --> 00:02:41,000 And I know that here rank is three your. 36 00:02:43,000 --> 00:02:45,000 Zero zero. 37 00:02:47,000 --> 00:02:49,000 You know, I mean, I think it's. 38 00:02:52,000 --> 00:02:54,000 I know, but I guess what? 39 00:02:55,000 --> 00:02:56,000 So this is how you can find out. 40 00:02:57,000 --> 00:02:57,000 All right. 41 00:03:00,000 --> 00:03:07,000 And there are some other function also in this. 42 00:03:08,000 --> 00:03:09,000 Mathematics. 43 00:03:10,000 --> 00:03:10,000 Linear algebra. 44 00:03:11,000 --> 00:03:16,000 So I just go to the linear algebra. 45 00:03:18,000 --> 00:03:24,000 So let's say I want to find out the inverse of you and I guess log it. 46 00:03:25,000 --> 00:03:27,000 I want to find out the inverse of this. 47 00:03:27,000 --> 00:03:27,000 My. 48 00:03:28,000 --> 00:03:34,000 I want to find out that on all of these metrics, I want to find over the metric square. 49 00:03:38,000 --> 00:03:39,000 Like this. 50 00:03:39,000 --> 00:03:41,000 You can use these functions. 51 00:03:41,000 --> 00:03:42,000 And you. 52 00:03:44,000 --> 00:03:45,000 Mathematics. 53 00:03:45,000 --> 00:03:46,000 Or you can perform. 54 00:03:47,000 --> 00:03:50,000 Different mathematical operations using these functions. 55 00:03:50,000 --> 00:03:55,000 Let's say I want to find over the eigenvalue of the matrix also. 56 00:03:56,000 --> 00:04:00,000 So this or here, this is the rank. 57 00:04:07,000 --> 00:04:12,000 It will provide me the eigenvalues for view and Matrix. 58 00:04:13,000 --> 00:04:18,000 Actually provide me the eigenvector for viewing matrix. 59 00:04:21,000 --> 00:04:24,000 It will provide me the inverse matrix. 60 00:04:27,000 --> 00:04:41,000 And over here, when you give me the principles of this, you in my tracks and you give me the URL of 61 00:04:41,000 --> 00:04:48,000 given my yes control you and this is my input. 62 00:04:48,000 --> 00:04:50,000 My six or here. 63 00:04:50,000 --> 00:04:51,000 This is my rank. 64 00:04:53,000 --> 00:04:55,000 This is my eigenvalues. 65 00:04:58,000 --> 00:04:58,000 Or here. 66 00:04:59,000 --> 00:05:03,000 This will provide me nine months of my university. 67 00:05:04,000 --> 00:05:07,000 It will provide me the cross bowls. 68 00:05:09,000 --> 00:05:11,000 It will provide me thus career. 69 00:05:14,000 --> 00:05:16,000 This will provide me the eigenvector. 70 00:05:19,000 --> 00:05:21,000 Okay so when I on Donovan Beck on. 71 00:05:24,000 --> 00:05:34,000 As you see in my picks, the lists and eddies that cross holes like or here or is in this first row 72 00:05:34,000 --> 00:05:37,000 and over here is normal for these over here. 73 00:05:38,000 --> 00:05:40,000 So this is the matrix transpose. 74 00:05:40,000 --> 00:05:42,000 And for here I was. 75 00:05:43,000 --> 00:05:45,000 These are the I didn't rehearse. 76 00:05:48,000 --> 00:05:51,000 Just increase the size and or hair. 77 00:05:53,000 --> 00:05:54,000 These are my values. 78 00:05:54,000 --> 00:05:56,000 Values are there. 79 00:05:57,000 --> 00:05:58,000 And over here. 80 00:05:58,000 --> 00:05:59,000 This is the matrix. 81 00:06:00,000 --> 00:06:01,000 So let's say. 82 00:06:03,000 --> 00:06:03,000 Just. 83 00:06:04,000 --> 00:06:05,000 We have to check. 84 00:06:07,000 --> 00:06:10,000 Operational transport's on track. 85 00:06:10,000 --> 00:06:14,000 So first, I want to find out mental health metrics. 86 00:06:14,000 --> 00:06:18,000 And I want to find out what are the mental transposed metrics. 87 00:06:19,000 --> 00:06:24,000 So for breakfast, was I just for linear algebra? 88 00:06:28,000 --> 00:06:29,000 And or. 89 00:06:29,000 --> 00:06:30,000 Here, this is my. 90 00:06:31,000 --> 00:06:32,000 So I just. 91 00:06:34,000 --> 00:06:43,000 And what metrics is my metrics or have I got to commend and hopefully this. 92 00:06:45,000 --> 00:06:55,000 And I want to focus on cross-border mechanics for foreign deployment to down photometric neutrophil 93 00:06:55,000 --> 00:06:58,000 metrics and all of this normal ligament. 94 00:06:59,000 --> 00:07:01,000 Then put matrix matrix. 95 00:07:01,000 --> 00:07:07,000 So let's check the effect of Task Force on Big Mac. 96 00:07:07,000 --> 00:07:13,000 So controlling E or here, this is my command, so. 97 00:07:13,000 --> 00:07:14,000 And I hit on Longbottom. 98 00:07:14,000 --> 00:07:21,000 As you see, there is no effect on that task force and the both the case is that commands. 99 00:07:23,000 --> 00:07:27,000 So for that one I just change the display for. 100 00:07:28,000 --> 00:07:28,000 Let's see. 101 00:07:29,000 --> 00:07:29,000 Okay. 102 00:07:29,000 --> 00:07:30,000 Stopping by. 103 00:07:31,000 --> 00:07:39,000 So as we see again or hear this play for America, I want to change this 14 day. 104 00:07:41,000 --> 00:07:41,000 Okay. 105 00:07:41,000 --> 00:07:46,000 So then if you don't run with them, let's say you have to continuously run this. 106 00:07:46,000 --> 00:07:50,000 And I want to change some value here to one. 107 00:07:51,000 --> 00:07:55,000 My point is, I'm all these values. 108 00:07:56,000 --> 00:08:01,000 I know the rank is on somebody and you can check that change or help. 109 00:08:01,000 --> 00:08:04,000 So this is how you can find out the rank. 110 00:08:04,000 --> 00:08:09,000 Okay, Matrix, how you can find over that determinant or matrix, how you can find out then what's 111 00:08:09,000 --> 00:08:09,000 my base? 112 00:08:09,000 --> 00:08:17,000 How you can find out the general and eigenvector and how you can make use of a given matrix so you can 113 00:08:17,000 --> 00:08:18,000 change your matrix. 114 00:08:19,000 --> 00:08:28,000 Or here I fixed by you and you can find out that these rank determinant transpose using matrix operations 115 00:08:29,000 --> 00:08:29,000 like.