The Best Hypernets Alternatives in 2026

The Datumbox framework is written in Java for developing machine learning and statistical applications.

FLAML provides a fast Python library for automated machine learning and tuning.

Kubeflow provides a machine learning toolkit for deploying workflows on Kubernetes.

FlexML offers an easy to use and flexible automated machine learning library for Python.

oneDNN provides a library of optimized deep neural network operations for oneAPI.

The linfa project provides a machine learning framework written in Rust.

A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.

Build machine learning applications with Delta, an open-source framework implemented in Rust.

The fenn Python framework supports machine learning workflows and LLM agents, with trainers, templates, logging, and configuration management.

Flower provides a federated AI framework for machine learning projects.

Train and run models with OneFlow, a scalable deep learning framework for distributed machine learning workloads.

Catniff provides JavaScript developers with a Torch-like deep learning framework.

DJL is a Java framework for running deep learning models across different engines.

PaddlePaddle provides a deep learning framework for training models across devices and platforms.

FATE supports federated learning through an industrial grade framework.

The MegEngine framework supports deep learning and automatic differentiation, according to its repository description.

Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.

Sagify describes its project as a way to work with large language models and machine learning more easily.

TPOT uses genetic programming to optimize machine learning pipelines in Python.

ORMB packages machine learning models as OCI artifacts, in a workflow described as Docker for ML models.

Merlin supports machine learning model management, deployment, and serving in Kubernetes environments.

Cog packages machine learning models into containers to support deployment across environments.

Build neural networks and support machine learning research with Sonnet, a library based on TensorFlow.

MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.