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Data Labeling

data labeling

Labelers must be extremely attentive because each mistake or inaccuracy negatively affects a dataset’s quality and the overall performance of a predictive model.

How to get a high-quality labeled dataset without getting grey hair? The main challenge is to decide who will be responsible for labeling, estimate how much time it will take, and what tools are better to use.

In appilux we tackle that burden for you with prices which are even less than crowdsourcing websites like Amazon Mechanical Turk or Clickworker.

Steps to make AI model fabulous

If there was a data science hall of fame, it would have a section dedicated to labeling. The labelers’ monument could be Atlas holding that large rock symbolizing their arduous, detail-laden responsibilities.

While labeling is not launching a rocket into space, it’s still serious business. Labeling is an indispensable stage of data preprocessing in supervised learning. Historical data with predefined target attributes (values) is used for this model training style. An algorithm can only find target attributes if a human mapped them.

data labeling 3

All Sorts

We do all the dirty stuff you want to annotate your data, audio, video, image classification etc

Trained Team

We have a team of trained people with proper qualifications for you to run the job

High Precision

Two independent annotators will check all inconsistent results with a supervisor

Best Prices

The price we offer is much less than what you can get with google, amazon, etc. Best Value with us.

Ask Anything!

Ask for specific guidelines regarding how we handle your data and we will look into it

Start Your AI Path With Us

Create an efficient machine learning pipeline on the cloud with AppiLux team of experts and focus on new opportunities that AI presents you on the fly
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