Worked on modernizing the CycleGAN example in the keras-team/keras-io repository to ensure compatibility with Keras 3 and the TensorFlow backend. The update involved replacing deprecated imports and layers with their Keras 3 equivalents and carefully adjusting the training configuration to 90 epochs to maintain model quality under the new API. This migration addressed the need for seamless upgrades for users transitioning to Keras 3, reducing potential friction. The work was implemented using Python and leveraged deep learning frameworks such as Keras and TensorFlow, with a focus on generative adversarial networks and up-to-date best practices in model development.