What is the difference between AI training and inference?

What is the difference between AI training and inference?

AI training is the process of teaching a model using data, while inference is when the model makes predictions based on new data.

Can you explain how training data is used during the training phase?

During training, the model learns patterns from the training data, adjusting its parameters to minimize errors in predictions.

What happens during the inference phase?

In the inference phase, the trained model takes new input data and applies what it learned to make predictions or decisions.

Are there any specific algorithms used for training?

Yes, common algorithms include gradient descent, decision trees, and neural networks, depending on the task.

How does the performance of a model change between training and inference?

Performance can vary; a model may perform well on training data but struggle with unseen data due to overfitting.