Inference is the correct answer because it is the AI process that occurs when a deployed model analyzes new data (such as an image) to make predictions or identify objects.
Inference:
In the context of machine learning, inference is the process of using a trained model to make predictions on new, unseen data.
When the deep learning model is deployed to production and receives a new image for analysis, it uses the learned patterns from the training phase to identify objects in the image. This is known as inference.
Why Option B is Correct:
Inference Process: Involves applying the trained model to real-world data (the new image) to identify objects.
Deployment Context: The model has already been trained, and the deployment to production indicates it is being used for inference.
Why Other Options are Incorrect:
A. Training: Refers to the process of teaching the model using historical data, not making predictions on new data.
C. Model deployment: Refers to the process of making a trained model available for use in production.
D. Bias correction: Is a process to adjust a model to minimize bias, not for analyzing new images.
