Keras

About Keras

High-level neural networks API designed for fast experimentation with deep neural networks. Runs on top of TensorFlow offering a user-friendly interface for building models.

Key Features

• 1High-level neural network API running on TensorFlow, JAX, or PyTorch
• 2Sequential and functional model APIs for simple and complex architectures
• 3Callbacks system for checkpointing, early stopping, and custom logging
• 4Keras Tuner for automated hyperparameter search
• 5Preprocessing layers for normalization, encoding, and augmentation

How Python Data Engineers Use Keras

Data engineers use Keras to prototype and deploy deep learning models quickly. The high-level API reduces boilerplate — defining a model, compiling with a loss and optimizer, and calling `.fit()` with a data pipeline is typically under 20 lines. Keras preprocessing layers are particularly useful for building self-contained models that include their own data transformation logic.