Labeling as service, what does it actually mean?
Data Labeling Service – an AI Platform which allows us to generate accurate and high-quality labels using Machine learning models on the collection of data.
Say, for example, you have a collection of images or videos taken in your garden or favorite landscape. You need to identify the flowers by name as you run the gallery. In this case, you can train the model to identify the flowers in the image by labeling their names. Similar way, you can train a model to identify all diseases or terminology from the collection of medical documents.
Is it a complex process?
Labeling training data acts as the first step in the machine learning development cycle under Computer Vision. Consider we need to train a machine learning model to identify a specified category of objects from the collection of data.
We would need to collect representation data samples which have to be classified and analyzed along with a Machine Learning algorithm for handling each sample.
How do the service benefit?
A report says, that about 80% of data scientists spend their time solely on creating and managing training data. This lag can be due to inappropriate tools, re-work on labeling, and no proper collaboration within the data science team.
You can accelerate the production with our robust data training solution for machine learning along with the best tooling, collaboration and integrated support.
Any dependencies? How do you work?
Yes, the Data labeling service will work perfectly with the following resources,
As initial step after receiving these resources along with service confirmation, our ML engineers shall start annotating items in the dataset according to the instructions provided. On completion of labeling, the dataset can be exported and used in further machine learning development.
Our Data labeling services shall replace the manual annotation process with automation via a user-friendly interface that eases the annotation and parameter defining process.
The solution provides configurable and intuitive interfaces that ease the annotation process by selecting the object or mapping the object (with box or polygons) and categorize them. Also, the solution shall allow collaboration of the task within the team and connect with cloud storage.