The Best Detecto Alternatives in 2026

LightlyTrain supports pretraining, fine-tuning, and distillation for computer vision models.

OpenMetricLearning provides metric learning pipelines, models, and a model zoo.

FEDOT automates machine learning model development through its modeling framework.

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

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

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

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

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

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.

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

DeepSpeed optimizes distributed training and inference for deep learning models.

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

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

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

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

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.

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

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

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

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.