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Keras (Standalone API)

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description Keras (Standalone API) Overview

Keras, as a high-level API, remains unparalleled for beginners and rapid prototyping. Its clean, sequential model definition makes building standard neural networks incredibly fast. While it is often integrated into TensorFlow, using it standalone allows developers to focus purely on model architecture without getting bogged down in backend specifics. It prioritizes developer experience above all else.

help Keras (Standalone API) FAQ

Can I use Keras without TensorFlow in 2024 and 2025?

Yes. Keras 3 (released in late 2023) is a multi-backend framework that works with JAX, TensorFlow, and PyTorch as its computational backend. You can install Keras standalone via pip and select your backend through the `KERAS_BACKEND` environment variable without depending on TensorFlow.

Is Keras still maintained now that François Chollet has moved on?

François Chollet, the original creator of Keras, stepped back from day-to-day development in recent years, but the project is actively maintained by the Keras team at Google and the open-source community. Keras 3 development continues with regular releases and multi-backend support.

How do I switch Keras to use JAX instead of TensorFlow as the backend?

Set the environment variable `KERAS_BACKEND=jax` before importing Keras in your script, or configure it programmatically via `keras.config.set_backend("jax")`. You will also need to install the `jax` pip package in your environment.

Is Keras good for beginners compared to PyTorch?

Keras is widely considered more beginner-friendly than raw PyTorch because it uses a simple Sequential or Functional API where you stack layers in a few lines of code. PyTorch offers more granular control over the training loop, which is valuable for research but can be overwhelming for someone just learning deep learning.

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