The Best Archai Alternatives in 2026

Katib automates machine learning on Kubernetes, including hyperparameter tuning and neural architecture search.

AutoGL provides automated graph learning through a machine learning framework and toolkit.

AutoKeras automates development of deep learning models through a machine learning library.

FEDOT automates machine learning model development through its modeling framework.

Enables single machine or distributed training and evaluation of deep learning models.

m2cgen converts machine learning models into native code for multiple programming languages without runtime dependencies.

Knet provides a deep learning framework developed at Koç University for building models.

neural-fortran provides a parallel framework for deep learning in Fortran.

PyTorch Geometric Temporal provides models and tools for spatiotemporal signal processing with neural learning.

mgl provides a machine learning library in Common Lisp, including neural networks and Gaussian processes.

Bender helps developers build neural networks for iOS using TensorFlow models and Metal.

autoai automates regression and classification modeling in Python through model search and hyperparameter tuning.

KerasTuner searches hyperparameters to optimize machine learning models built with Keras.

PyTorch Lightning helps pretrain and fine-tune AI models across one or many GPUs with minimal code changes.

Use Learnergy, a Python library for training and working with energy-based machine learning models.

PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.

This Common Lisp repository collects algorithms for online linear classification.

TensorFlow Model Optimization provides Keras and TensorFlow tools for model quantization and pruning.

Karate Club offers algorithms for unsupervised learning on graph data in Python.

doddle-model is an in-memory machine learning library for Scala, built on Breeze with a scikit-learn-like API using typeclasses.

AutoGluon provides tools for automated machine learning and model development.

This repository implements random forest models in Common Lisp for classification tasks.

Detecto supports building and training computer vision models with the PyTorch machine learning framework.

This metric-learn repository contains Python implementations of metric learning algorithms.