Data Labeling In Machine Learning
The process of assigning labels to raw data, transforming it into a structured format for training machine learning models. This step is essential for models to classify data, recognize patterns, and make predictions.
Areas of application
- Computer Vision
- Natural Language Processing
- Speech Recognition
- Recommendation Systems
- Predictive Maintenance
Example
For example, in image recognition, data labeling involves annotating images with relevant information such as objects, actions, or emotions. This allows the machine learning model to learn the patterns and relationships between these features and their corresponding labels.