Original subtitles

Hello and welcome to this video.

In this video we will explain about datasets.

YOLO is a supervised learning object detection model.

Supervised learning is a learning technique that employs labeled data.

In supervised learning.

The data to be used must have several characteristics.

Relevant.

Proper label.

The data used to train the deep learning model must be relevant to the problem to be solved.

For example, if we want to detect the car on the highway, the data must be an image of a car on the

highway.

Make sure the data use is properly label.

All objects are labeled and non non object is labeled as object.

After that how to find data sets.

There are two methods.

The first method is to collect information by taking photographs.

However, this method takes longer and requires us to annotate the data after we obtain it.

The second method is looking for open label datasets that are publicly available.

One that is frequently used is chemical.

How to find it, they said on cable.

The first step is to launch a browser and navigate to the following URL.

Next signing to cargo.

If you do not already have an account, you can create one.

In this video, I'll sign into Kaggle with my Google account.

Click sign in with Google.

Since the Google account you want to use.

After successfully signing in click datasets in the following search box type in the keyword dataset

you're looking for.

In this example, we'll be looking for a dataset of face masks.

This is the search result.

When choosing a data set, there are several factors to consider.

The first consideration is usability.

The second is the data sets ready.

We tried to select a dataset with high usability and ready.

The license is the next point to consider.

Customized to your needs.

If you use the data set for commercial purposes, make sure that the data set is licensed for commercial

use.

To download the dataset, click the download button over here.

Wait until the download is finished.

This is a downloaded dataset of face masks.

See you in the next video.