DATA SCIENCE 101: Data Labeling
Your business has a massive amount of unlabeled data which cannot be effectively used in Machine Learning models. In order to build an accurate learning system, the data must be labeled through the process of Data labeling.
What is Data Labeling?
Data labeling refers to the process of adding context to different types of data such as text, images and audio. Once completed, the labeled data will be used to train a machine learning model to recognize patterns in similar data sets in the future.
For example, we label to indicate a dog and a cat in an image, so the models can learn the common features of a cat and a dog to identify them correctly in other unlabeled data.
How can we label data?
The Data Labeling process can be done both manually and automatically. Generally, companies have four options to Label their data:
- In-house staff: your own employees, either full-time or part-time.
- Managed teams: a team of data labelers, trained and managed by a third party company.
- Contractors: temporary or freelance workers.
- Crowdsourcing: on-demand workforce provided by Crowdsourcing platforms like MTurk
If you are interested in Data Sciences and Data Labeling Services, don’t hesitate to visit our website:
https://data-ai.vn/services/data-labeling/
