Inference
2024 | AI Dictionary
What is Inference: The process of making predictions or decisions based on a trained model using learned parameters to evaluate new data.
What is Inference?
Inference in machine learning refers to the process of making predictions or decisions based on a trained model . It involves using the learned parameters of a model to evaluate new, unseen data and generate outcomes such as classifications, predictions, or recommendations.
Types of Inference
- Forward Inference: The model uses input features to predict an output.
- Backward Inference: Involves working backward to deduce potential causes or parameters that led to a specific outcome.
Applications of Inference
- Recommendation Systems: Used to predict user preferences based on past behavior, such as in Netflix or Amazon.
- Image Classification: Identifies objects or features in images based on the trained model.
- Speech Recognition: Converts spoken language into text using inference models trained on voice data.
Example of Inference
In an image classification task, a model trained on labeled images of cats and dogs can make an inference by predicting whether a new image shows a cat or a dog, based on the features it has learned from the training data.
Did you liked the Inference gist?
Learn about 250+ need-to-know artificial intelligence terms in the AI Dictionary.