Developer guides

Our developer guides are deep-dives into specific topics such as layer subclassing, fine-tuning, or model saving. They're one of the best ways to become a Keras expert.

Most of our guides are written as Jupyter notebooks and can be run in one click in Google Colab, a hosted notebook environment that requires no setup and runs in the cloud. Google Colab includes GPU and TPU runtimes.

Available guides

• The Functional API
• The Sequential model
• Making new layers & models via subclassing
• Training & evaluation with the built-in methods
• Customizing fit() with JAX
• Customizing fit() with TensorFlow
• Customizing fit() with PyTorch
• Writing a custom training loop in JAX
• Writing a custom training loop in TensorFlow
• Writing a custom training loop in PyTorch
• Serialization & saving
• Customizing saving & serialization
• Writing your own callbacks
• Transfer learning & fine-tuning
• Distributed training with JAX
• Distributed training with TensorFlow
• Distributed training with PyTorch
• Distributed training with Keras 3
• Migrating Keras 2 code to Keras 3