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    You are at:Home»FAQ»Data Annotation and its Role In Machine Learning
    FAQ

    Data Annotation and its Role In Machine Learning

    Brady CottonBy Brady CottonOctober 21, 2021
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    Data normally is the backbone of all aided machine learning projects. The additional data you have, the chances of desired results will be greater however, only data is not going to work. One has to get data annotated in order to make AI to identify different aspects in any image and other workings. Artificial intelligence and machine learning are some of the most considered fields nowadays. Because they offer incredible benefits to the country’s economy and technological success. But in order to work on them we must annotate the data to make machines recognize and consume the data. You can do labeling data here!

    Data annotation is not an option for machine learning. It’s an essential source to make the technologies like AI and machine learning work smoothly. Furthermore, data annotation is a very complicated and time-taking process. And it takes a lot of time to get the data annotated perfectly. Because any unintentional mistake can even produce biased results. The better the data annotated the more it will be able to understand what it’s trying to explain, image or human language. Every firm cannot get their Data annotated by themselves, instead, they outsource in order to meet the accuracy and save time.

    Types of Data annotation

    AI Data annotation is not restricted to one specific method. But one can get their data annotated in different types such as images, audio, and even video. Let’s have a brief introduction to them.

    Image annotation:  this is the background annotation needed behind the image to understand the work and its goal. For instance, face recognition mobile locks identify one’s nose, eyes and other facial features to work. This is an image annotation that includes identifiers and keywords included. Filters also work on every face regardless of its shape because of annotations.

    Audio Annotation: Sounds can also be annotated with the help of keywords and proper metadata. This aids in recognizing audio in a more meaningful form. For e.g Virtual assistance in android, apple and other technologies work due to the audio annotation.

    Video Annotation: Similar to image annotation, video annotation also helps the computer to understand objects. Precise annotation in the video can help in achieving accurate results and identification quickly.

    Role of Data Annotation

    Search engines must provide users with comprehensive information. Their algorithms must process high volumes of labeled datasets to offer the proper answer to try and do that. Take, as an example, Microsoft’s Bing. Since it caters to multiple markets, the seller must confirm that the results the computer program would supply would match the user’s culture, line of business, and so on.

    Data Annotation is a time-consuming process and it takes almost 80% of the time in preparation of data. It is difficult because any small mistake can cause errors and changes in the result. There must be no ambiguity while understanding the image, text, video. Therefore, it must be done without the chance of any error. The main aspect of annotating data is to label data. Labeling data is one of the initial steps in any data pipeline. Plus, the act of labeling data can ends up in cleaner data and extra areas of opportunity.

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