The Best FEDOT Alternatives in 2026

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.

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

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

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

Guild AI automates and optimizes machine learning experiments while tracking each run.

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

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

Learnergy is a Python library for energy-based machine learning models.

ML_Forgex trains, evaluates, and predicts with machine learning models on cleaned datasets.

Auto_ViML builds multiple machine learning models with a single line of code.

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

PEFT provides parameter-efficient fine-tuning methods for adapting pretrained machine learning models.

Archai supports neural architecture search with fast, reproducible, and modular research tools.

Lightwood builds and customizes machine learning pipelines using a declarative JSON-AI syntax.

EvalML builds, optimizes, and evaluates machine learning pipelines with automated data checks and objective functions.

numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.

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

DeepSpeed optimizes distributed training and inference for deep learning models.

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

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.

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

metric-learn provides Python implementations of metric learning algorithms.