{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering"}],"enrichment":{"capability":"Keras 3 is a multi-backend deep learning framework supporting JAX, TensorFlow, PyTorch, and OpenVINO, enabling you to build and train neural networks for computer vision, NLP, audio, timeseries, and recommender systems.","skillfed_tags":["multi-backend","deep-learning","neural-networks"],"use_cases":["Build computer vision models (CNNs, transformers) that run on JAX for research or on TensorFlow for production.","Migrate existing tf.keras code to run on PyTorch or JAX without rewriting the model definition.","Train NLP models (text classification, sequence-to-sequence) with a unified API across multiple frameworks.","Deploy inference-only models using the OpenVINO backend for edge or embedded systems.","Write backend-agnostic custom layers and metrics that work across TensorFlow, JAX, and PyTorch.","Prototype on CPU with PyTorch, then scale to TPUs with JAX using the same model code."],"what_it_does":"Keras 3 is a high-level deep learning framework that abstracts away backend differences, letting you write model code once and run it on JAX, TensorFlow, PyTorch, or OpenVINO. It provides a familiar API for building and training neural networks across domains\u2014computer vision, NLP, audio, timeseries, and recommendation systems\u2014while letting you choose the backend that best fits your performance or deployment needs.\n\nThe framework is designed as a drop-in replacement for tf.keras when using the TensorFlow backend, and supports both high-level Keras workflows and lower-level custom components. It depends on numpy, h5py, rich, absl-py, namex, optree, ml-dtypes, and packaging. You must install and configure a backend separately before use, and the backend cannot be changed after import.","worth_installing":"Yes. Keras 3 is actively maintained, widely adopted (19.5M monthly downloads), has no known vulnerabilities, and offers genuine value if you want to avoid framework lock-in or need to switch backends. Install it if you're building deep learning models and want flexibility; skip it only if you're committed to a single framework and don't need Keras's high-level API."},"id":"keras","links":{"html":"https://skillfed.io/packages/keras","md":"https://skillfed.io/packages/keras.md","pypi":"https://pypi.org/project/keras/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-29","license_spdx":null,"license_treatment":"permissive","name":"keras","python_support":"supports_current","summary":"Multi-backend Keras"},"popularity":{"monthly_downloads":19542671,"position":1061,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"3.15.1"}