Lightwood builds and customizes machine learning pipelines using a declarative JSON-AI syntax.
The Best emel Alternatives in 2026
Looking for something like emel? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 21 are open source.
emel provides functional machine learning tools for developers using the Erlang ecosystem.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Lightwood | — | Yes | — |
| 2 | Bender | — | Yes | iOS |
| 3 | Learnergy | — | Yes | — |
| 4 | doddle-model | — | Yes | — |
| 5 | AutoGluon | — | Yes | — |
| 6 | FEDOT | — | Yes | — |
| 7 | Petastorm | — | Yes | — |
| 8 | Detecto | — | Yes | — |
| 9 | Katib | — | Yes | — |
| 10 | hyperopt | — | Not stated | — |
All emel alternatives
Bender helps developers build neural networks for iOS using TensorFlow models and Metal.
Use Learnergy, a Python library for training and working with energy-based machine learning models.
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.
FEDOT automates machine learning model development through its modeling framework.
Enables single machine or distributed training and evaluation of deep learning models.
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.
hyperopt
github.com/hyperopt/hyperopt-sklearnhyperopt-sklearn uses hyperparameter optimization to select machine learning algorithms for scikit-learn.
ML_Forgex trains, evaluates, and predicts with machine learning models on cleaned datasets.
mgl provides a machine learning library in Common Lisp, including neural networks and Gaussian processes.
Auto_ViML builds multiple machine learning models with a single line of code.
AutoGL provides automated graph learning through a machine learning framework and toolkit.
Guild AI automates and optimizes machine learning experiments while tracking each run.
m2cgen converts machine learning models into native code for multiple programming languages without runtime dependencies.
EvalML builds, optimizes, and evaluates machine learning pipelines with automated data checks and objective functions.
KerasTuner searches hyperparameters to optimize machine learning models built with Keras.
ParaMonte
github.com/cdslaborg/paramonteParaMonte provides parallel Monte Carlo and machine learning tools across several programming languages.
AutoKeras automates development of deep learning models through a machine learning library.
numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.
Karate Club offers algorithms for unsupervised learning on graph data in Python.
Knet
github.com/denizyuret/Knet.jlKnet provides a deep learning framework developed at Koç University for building models.
neural-fortran provides a parallel framework for deep learning in Fortran.
Alternatives to similar tools
What is the best alternative to emel?
Are there open-source alternatives to emel?
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
























