Keras

Health v2 · maintenance only

Adoption not part of the score

64253 stars · 19764 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Keras 3 is a multi-backend deep learning framework that runs on JAX, TensorFlow, PyTorch, and OpenVINO, providing a high-level API for building and training neural networks. It supports workloads from laptops to large GPU/TPU clusters across computer vision, NLP, audio, and timeseries tasks.

Use cases

• build and train neural networks in python
• train deep learning models on gpu or tpu clusters
• switch between tensorflow pytorch and jax backends
• build computer vision or nlp models with a high-level api
• forecast timeseries with deep learning
• run model inference with openvino

When to choose

• you want a simple, high-level API for deep learning in Python
• you need to train models across multiple hardware backends
• you want to scale from a laptop to datacenter GPU/TPU clusters
• you prefer easy-to-debug eager execution with PyTorch or JAX

When to avoid

• you need low-level control over training loops and graph internals
• you work primarily on Windows without WSL2
• you need inference-only deployment without a backend framework

Facets

library · maturity stable

deep-learning machine-learning llm-training data-science deep-learning machine-learning data-science computer-vision python neural-networks multi-backend tensorflow pytorch jax openvino model-training high-level-api natural-language-processing linux macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="keras-team/keras")