ecosystem.md

The Keras ecosystem

The Keras project isn't limited to the core Keras API for building and training neural networks. It spans a wide range of related initiatives that cover every step of the machine learning workflow.

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KerasHub

KerasHub Documentation - KerasHub GitHub repository

KerasHub is a pretrained modeling library that aims to be simple, flexible, and fast. The library provides Keras implementations of popular model architectures, paired with a collection of pretrained checkpoints. Models can be used with text, image, and audio data for generation, classification, and many other built-in tasks.

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KerasRS

KerasRS Documentation - KerasRS GitHub repository

Keras Recommenders is a library for building recommender systems on top of Keras. It provides a collection of building blocks which help with the full workflow of creating a recommender system.

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KerasTuner

KerasTuner Documentation - KerasTuner GitHub repository

KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search algorithms.

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AutoKeras

AutoKeras Documentation - AutoKeras GitHub repository

AutoKeras is an AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible for everyone. It provides high-level end-to-end APIs such as ImageClassifier or TextClassifier to solve machine learning problems in a few lines, as well as flexible building blocks to perform architecture search.

import autokeras as ak

clf = ak.ImageClassifier()
clf.fit(x_train, y_train)
results = clf.predict(x_test)

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BayesFlow

BayesFlow documentation - BayesFlow

A Python library for amortized Bayesian workflows using generative neural networks, built on Keras 3, featuring:

• A user-friendly API for rapid Bayesian workflows

• A rich collection of neural network architectures

• Multi-backend support via Keras 3: You can use PyTorch, TensorFlow, or JAX