Top 10 Data Labeling Tools for 2022

The data labeling aspects are crucial in machine learning and AI development. A structured set of data training in an ML system is necessary. It takes a lot to create accurately labeled datasets. Data labeling tools are very useful because they can automate labeling, which is extremely tedious.

These tools allow for easier collaboration and quality control during the entire dataset creation process. It is possible to create a training dataset using any data type and connect it with your ML pipelines. In this article, we will explore the top 10 data labeling tools.

Top 10 Data Labeling Tools for 2022

1. Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth, a state-of-the-art data labeling service by Amazon, is available. This tool simplifies the creation of machine learning datasets by providing a fully managed data-labeling service.

Ground Truth makes it easy to create highly accurate training data sets. Ground Truth has a built-in workflow that allows you to label your data in minutes with high accuracy. This tool supports different types of labeling output, including text, images video, and 3D cloud points.

Labeling features like automatic 3D cuboid snapping, removals of distortion in 2D images, and auto-segment tools make labeling easy and efficient. These features greatly reduce the time required to label the dataset.

Key of features:

• Amazon allows you to enter raw data.
• Use the built-in workflow to create automatic labeling tasks.
• Select the right labeler from the group.
• Assistive labeling feature for labels
• Create accurate training datasets.

These are the benefits:

• It is easy to use and automatic.
• It increases data labeling accuracy.
• This feature allows for a significant reduction in time.

2. Label Studio

Label Studio is a web platform that allows you to explore multiple data types and offer data labeling services. It is built with a mixture of MST and React as the frontend and Python as its backend.

It allows data labeling of all data types: text, images, and video as well as audio and time series. The resulting datasets are highly accurate and can be easily used in ML applications. It is available from all browsers. It is available as precompiled CSS/JS scripts that can be used on all browsers. You can embed Label Studio UI in your applications.

This tool is used to accurately label and create optimized datasets.

Key of features:

• Data is taken from different APIs, files, and HTML markup.
• Pipelines data to a labeling structure that includes three main sub-processes
• Data entry task that collects data from different sources.
• The final step results in labeling in JSON format.
• Optional labeling results can be obtained in JSON format by the prediction process.
• Machine learning backend uses efficient and popular ML frameworks to automatically create precise datasets.

These are the benefits:

• Data labeling for different types of data is possible.
• It is easy to use and it works automatically
• It is accessible from any web browser and also can be embedded in personal applications.
• High-level dataset with precise labeling workflow.

Originally published on The Tech Trend