How does Keras handle model training and evaluation compared to other frameworks?

Keras simplifies model training and evaluation through methods like fit() for training, evaluate() for testing, and predict() for inference. These high-level abstractions streamline the workflow, allowing developers to focus on refining the model rather than implementing low-level details. Other frameworks, like PyTorch, often require manual loops for similar tasks, which can be more complex but provide greater control.