1 00:00:00,660 --> 00:00:02,340 This is over, no real fighting. 2 00:00:03,240 --> 00:00:09,190 This is good to solve and input output feting problem with a two layer feet forward. 3 00:00:09,480 --> 00:00:16,380 No, we're all network feed is the architecture of this model of this network network. 4 00:00:16,710 --> 00:00:21,690 And it has only two layer, one hidden layer and other outputs layer. 5 00:00:22,650 --> 00:00:30,690 But we can adjust the number of neurons here for the hidden layer, only for the output layer it will 6 00:00:30,690 --> 00:00:32,070 get only one. 7 00:00:33,070 --> 00:00:34,630 I will explain it later. 8 00:00:34,830 --> 00:00:36,840 So let's take a look at this one again. 9 00:00:37,090 --> 00:00:39,120 We have input the input. 10 00:00:39,420 --> 00:00:41,700 We'll get a specific way here. 11 00:00:41,700 --> 00:00:48,720 We can adjust the weight, adjust the number of neurons in this heat and LEGARE then the output is going 12 00:00:48,720 --> 00:00:51,730 to another layer with a specific rate. 13 00:00:51,900 --> 00:00:54,960 And finally, we will have our output. 14 00:00:55,470 --> 00:00:57,960 There are some explanation here as well. 15 00:00:58,450 --> 00:01:00,930 You can just read them for your information. 16 00:01:01,200 --> 00:01:02,400 Some of them are important. 17 00:01:02,400 --> 00:01:07,000 For example, this network is using back propagation algorithm. 18 00:01:07,020 --> 00:01:08,520 This is a name of algorithm. 19 00:01:08,520 --> 00:01:13,400 Death has been used for these neural network beta next. 20 00:01:13,410 --> 00:01:18,630 And here this is the part that we need to select the data. 21 00:01:19,530 --> 00:01:26,160 We can select our input and we can select our target data or our output data. 22 00:01:26,370 --> 00:01:35,700 If I choose this one, if I just click on inputs, I can see the variables from working space X and 23 00:01:35,700 --> 00:01:40,260 Y, so I'm going to choose X for my input and the targets. 24 00:01:41,220 --> 00:01:42,610 Let's just click on it. 25 00:01:42,630 --> 00:01:44,610 If you have another data. 26 00:01:44,610 --> 00:01:52,080 I just generated some samples in a matlab, but usually you will have some data maybe in Excel, Fi 27 00:01:52,380 --> 00:01:53,580 or any other files. 28 00:01:53,580 --> 00:01:59,450 You can just click to import your data, input your inputs and import your target data. 29 00:01:59,760 --> 00:02:01,910 Our target data is why? 30 00:02:01,920 --> 00:02:08,580 So I'm going to choose why samples are in Imitrex columns or in Imitrex rows. 31 00:02:09,210 --> 00:02:10,080 What does it mean? 32 00:02:10,440 --> 00:02:13,820 Let's back to our command window. 33 00:02:14,160 --> 00:02:17,970 I'm going to just type Steel C to clear this work. 34 00:02:18,180 --> 00:02:20,610 Now let's see what over X input. 35 00:02:20,610 --> 00:02:23,340 Just Type X and inter. 36 00:02:24,270 --> 00:02:33,210 These are the inputs I have 20 samples are just generated, 20 samples for X and then my Y, which is 37 00:02:33,210 --> 00:02:34,530 the size of X. 38 00:02:34,530 --> 00:02:36,780 Just click on Y and enter. 39 00:02:37,530 --> 00:02:41,910 I have twenty output of twenty sample for Y as well. 40 00:02:42,280 --> 00:02:49,350 You can also see X and Y together, X and Y for each sample. 41 00:02:50,880 --> 00:02:52,860 Here it is X and Y. 42 00:02:52,860 --> 00:02:55,700 By looking at this one, what can you understand. 43 00:02:55,710 --> 00:02:59,970 Do you think they are now rows or do you think they're over samples. 44 00:02:59,970 --> 00:03:01,710 Over data on columns. 45 00:03:02,770 --> 00:03:05,870 OK, I assume that you are giving me a correct answer. 46 00:03:06,180 --> 00:03:06,870 They are. 47 00:03:06,870 --> 00:03:07,800 And columns. 48 00:03:07,980 --> 00:03:08,700 Look at this one. 49 00:03:08,700 --> 00:03:12,840 This is one sample, this is another sample and we have 20 of them. 50 00:03:13,230 --> 00:03:14,790 These are inputs and outputs. 51 00:03:15,030 --> 00:03:20,460 If you are using an Excel file, usually an Excel file, we do something else. 52 00:03:20,700 --> 00:03:22,560 Let's take a look at this example. 53 00:03:23,430 --> 00:03:27,800 This is how we usually put the data on the Excel flight. 54 00:03:28,320 --> 00:03:36,360 This is a column for our inputs, another column for Y and output, meaning each sample will be here 55 00:03:36,390 --> 00:03:37,950 under row. 56 00:03:38,340 --> 00:03:40,640 This is one road, second row, third road. 57 00:03:40,770 --> 00:03:45,530 If your data is something like that, then you need to choose the road metrics route. 58 00:03:45,870 --> 00:03:53,970 But for our example, which is our samples are on the columns here, as you can see. 59 00:03:54,720 --> 00:04:02,070 And the first row in this part is input X, second row is output Y. 60 00:04:02,660 --> 00:04:04,320 Let's back to that. 61 00:04:04,330 --> 00:04:09,840 We're waiting to hear I can see Matrix columns. 62 00:04:09,930 --> 00:04:12,060 It has been selected as default. 63 00:04:12,060 --> 00:04:13,410 I'm not going to change it. 64 00:04:13,420 --> 00:04:14,820 Let's leave it there. 65 00:04:15,120 --> 00:04:16,350 What else do we have? 66 00:04:16,560 --> 00:04:19,740 It's a summary which gives us some information. 67 00:04:19,740 --> 00:04:25,800 Input X is one to twenty metrics representing a static data. 68 00:04:26,010 --> 00:04:28,020 Twenty samples of one element. 69 00:04:28,560 --> 00:04:32,580 We have another element which it also has twenty samples. 70 00:04:32,940 --> 00:04:35,910 That's just click on next and go to the next part.