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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:02,100 --> 00:00:03,750 Hello and welcome to this video. 2 00:00:03,780 --> 00:00:06,360 In this video we will explain about datasets. 3 00:00:08,180 --> 00:00:11,180 YOLO is a supervised learning object detection model. 4 00:00:11,210 --> 00:00:14,660 Supervised learning is a learning technique that employs labeled data. 5 00:00:17,110 --> 00:00:18,400 In supervised learning. 6 00:00:18,400 --> 00:00:21,100 The data to be used must have several characteristics. 7 00:00:22,100 --> 00:00:22,910 Relevant. 8 00:00:24,410 --> 00:00:25,310 Proper label. 9 00:00:26,510 --> 00:00:30,740 The data used to train the deep learning model must be relevant to the problem to be solved. 10 00:00:31,070 --> 00:00:35,810 For example, if we want to detect the car on the highway, the data must be an image of a car on the 11 00:00:35,810 --> 00:00:36,440 highway. 12 00:00:37,210 --> 00:00:39,430 Make sure the data use is properly label. 13 00:00:41,230 --> 00:00:45,010 All objects are labeled and non non object is labeled as object. 14 00:00:51,200 --> 00:00:53,240 After that how to find data sets. 15 00:00:53,750 --> 00:00:55,100 There are two methods. 16 00:00:56,930 --> 00:01:00,350 The first method is to collect information by taking photographs. 17 00:01:00,380 --> 00:01:04,819 However, this method takes longer and requires us to annotate the data after we obtain it. 18 00:01:04,849 --> 00:01:08,870 The second method is looking for open label datasets that are publicly available. 19 00:01:08,870 --> 00:01:10,820 One that is frequently used is chemical. 20 00:01:15,700 --> 00:01:17,430 How to find it, they said on cable. 21 00:01:19,680 --> 00:01:23,270 The first step is to launch a browser and navigate to the following URL. 22 00:01:25,930 --> 00:01:27,610 Next signing to cargo. 23 00:01:29,800 --> 00:01:32,470 If you do not already have an account, you can create one. 24 00:01:35,600 --> 00:01:38,600 In this video, I'll sign into Kaggle with my Google account. 25 00:01:39,960 --> 00:01:41,430 Click sign in with Google. 26 00:01:43,970 --> 00:01:45,950 Since the Google account you want to use. 27 00:01:54,770 --> 00:02:00,350 After successfully signing in click datasets in the following search box type in the keyword dataset 28 00:02:00,350 --> 00:02:01,250 you're looking for. 29 00:02:02,430 --> 00:02:05,790 In this example, we'll be looking for a dataset of face masks. 30 00:02:12,510 --> 00:02:13,890 This is the search result. 31 00:02:16,970 --> 00:02:20,250 When choosing a data set, there are several factors to consider. 32 00:02:20,270 --> 00:02:22,310 The first consideration is usability. 33 00:02:22,340 --> 00:02:24,200 The second is the data sets ready. 34 00:02:25,460 --> 00:02:29,030 We tried to select a dataset with high usability and ready. 35 00:02:31,360 --> 00:02:33,580 The license is the next point to consider. 36 00:02:42,220 --> 00:02:43,620 Customized to your needs. 37 00:02:43,630 --> 00:02:48,460 If you use the data set for commercial purposes, make sure that the data set is licensed for commercial 38 00:02:48,460 --> 00:02:49,060 use. 39 00:02:53,940 --> 00:02:57,020 To download the dataset, click the download button over here. 40 00:02:57,030 --> 00:02:58,890 Wait until the download is finished. 41 00:03:13,280 --> 00:03:15,800 This is a downloaded dataset of face masks. 42 00:03:17,080 --> 00:03:18,520 See you in the next video. 3618