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Data Labeling Platform - Skyl

Data Labeling Platform

Skyl's data labeling platform allows you to quickly annotate and label data to suit your machine learning needs.

Data labeling is the process of attaching meaning to different types of digital data like audio files, text images, videos and more within the customer care industry.

That means your support team digitally assigns meaning by listening to call recordings or viewing chat logs and labeling specific components of each interaction.

Once the data is labeled, it's used for training advanced algorithms to recognize patterns in future similar data sets.

Algorithms can be designed to recognize opportunities for improvement or automation within processes. Identify and alert team leads that an agent needs help with a call. Provide agents with likely solutions to customer issues. Anticipate follow up concerns related to a customer's current issue, suggest relevant products or service upgrades and more.

As data is continuously collected, labeled and integrated into the algorithm training process, a more intelligent customer experience emerges that makes for better service, which makes for happier customers.

Related: Download this comprehensive cheat sheet to deploy machine learning on  time and on budget →

Table of Contents

Skyl- The Data labeling platform features

    1. Build high quality labeled data sets

    2. Data labeling for Image classification

    3. Data labeling - Named entity extraction


Skyl- The Data labeling platform features

1. Builds high quality labeled data sets

A significant time in machine learning projects is spent in data labeling. Skyl's data labeling platform can help in getting this done quicker and better thus reducing ML project completion times. Skyl’s Data Labeling platform provides data scientists to build great  machine models through faster iteration cycles and powerful tooling.

2. Data labeling for Image classification

With Skyl, you can quickly annotate and label images so that they can be used for machine learning. Skyl provides and easy to use interface for image data labeling. In the image below, you can see an example of image labeling where chest x-ray images are labeled for pneumonia detection.

Pneumonia detection using Skyl-1

Data labeling for image classification

3. Data labeling - Named entity extraction

NER (Named entity extraction stands for the process of extraction named entities from unstructured text). With Skyl.ai's NER labelling jobs, you can create jobs that make it  extremely easy to label, tag and annotate text in an interface that  unifies all your labelling jobs in one place.

Check out the various solutions that can be built using Sky Platform here.

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