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What is Annotation in Machine Learning and Types of Data Annotation in ML?

  • 5 August 2022
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Annotation means, in machine language simply making the things visible, recognizable or understandable in images, pictures, documents and videos by highlighting or marking or adding footnotes or metadata. And these annotated contents are when used in machine learning becomes the training data for algorithm to learn the different patterns in the data and utilize the same.

 

Data Annotation in Machine Learning


Annotation consists different types of data are annotated as per the machine learning model need and compatibility. And such data consists text, images and videos that contains the useful information about the object of interest that are annotated to make it recognizable to machines through NLP, NLU and computer vision technology used to train the AI-based models.

 

Text Annotation in Machine Learning


The language, speech and voice recognition based AI models need data sets that can help them to understand the human language and communication process on a specific topic. Text Annotation, Audio Annotation and NLP Annotation are the leading techniques basically done to create such data sets. Text annotation is performed with added metadata and notes to make each word, phrases in the sentence understandable to NLP based machine learning or AI models.

 

NLP & Audio Annotation in Machine Learning

In machine learning to recognize the human voice NLP annotation and audio annotation is done to create the training data sets for machine learning. Chatbot applications and virtual assistant devices are the leading language based AI systems need training data for machine learning. The human voice of a specific topic conversation is annotated with added metadata to make the conversations understandable to machines and become capable enough to talk with humans in real-life.

 

Image Annotation in Machine Learning


Similarly, for visual perception based AI models, image annotation is the best way to make the various objects recognizable in the environment with precise detection of such things in various scenarios. And there are image annotation techniques followed to annotate the objects in interest in different ways.

Bounding box, semantic segmentation, polygon and cuboid annotations are the leading image annotation techniques used to annotate the different types of objects for machine learning.

 

Video Annotation in Machine Learning


To detect the moving objects in the real-life scenario, video annotation is the best way to annotate such things. The moving object is annotated frame-by-frame from starting to end precisely using the best tools and techniques. Video annotation is useful for self-driving cars and drones that moves and other objects also seems moving hard to recognize. But with the help of video annotation such moving objects can be easily recognized by visual perception based AI models.

 

How to Get Annotation Services for Machine Learning?


Annotating the different types of data is not possible for a single person, you need different professionals to annotate the data as per the customize needs. A text annotators would be not able to annotate the images, or video annotators would be not able to annotate the texts. Hence, you can get in touch with data annotation companies where well-trained and experienced annotators work in the team to perform the text, video and image annotation tasks with high accuracy.


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