What is the difference between training and inference in Keras?

Updated May 16, 2026

Short answer

Training updates weights; inference uses trained model for predictions.

Deep explanation

During training, gradients are computed; during inference, model is used in forward pass only.

Real-world example

Deploying chatbot after training phase.

Common mistakes

  • Applying dropout during inference.

Follow-up questions

  • Is backprop used in inference?
  • Why inference is faster?

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