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Training & fine-tuning

Keras

Keeps a consistent model-development interface across multiple major deep-learning backends.

64,344 stars

Overview

Research summary

Keras provides high-level APIs for constructing, training and evaluating neural networks across several numerical backends. Developers can apply common model-building patterns to computer vision, language, audio, recommendation and other machine-learning tasks. Its current design supports JAX, TensorFlow and PyTorch for training, with OpenVINO documented for inference-only use. Backend choice affects execution and supported operations, while the Keras interface provides a common development surface. The repository contains the framework implementation rather than the pretrained weights of every compatible model.

Repository summary

Stars
64,344
Open issues
Unavailable
Last push
2026-10-02
Commits, 90 days
Unavailable
Repository activity
Not scored
Version
Unavailable

Recorded catalogue figures. View repository data and provenance →

Classification

Pricing & services

Paid services unknown

Whether the provider offers paid products or services has not been established.

Licence scope

Implementation

Recorded implementation details and interfaces for Keras.

Implementation details

Python library and supporting tools

Languages
Python
Repository type
source

Recorded interfaces and capabilities

Licence scope

Repository

Repository snapshots, release information and recorded maintenance signals.

Repository snapshot

keras-team/keras ↗

Stars
64,344
Open issues
Unavailable
Last push
2026-10-02
Commits, 90 days
Unavailable
Repository activity
Not scored
Archived
Not recorded

Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).

Maintenance and provenance

Catalogue snapshot
2026-10-06
Stars source
Recorded fallback
Last push source
Recorded fallback

Documentation

Recorded references and research provenance for this entry.

Recorded sources 5

Research metadata

Research date
2026-10-02
Catalogue snapshot
2026-10-06

Community & social 1 channels

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