Selection — 3 881

Machine Learning Toolkit for Kubernetes.

Resource scheduling and cluster management for AI.

An effortless infrastructure for machine learning built on the top of Kubernetes.

One-click machine learning deployment (LLM, text-to-image and so on) at scale on any cluster (GCP, AWS, Lambda labs, your home lab, or even a single machine).

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

An MLOps/LLMOps platform for model building, evaluation, and fine-tuning.

Workflow engine for Kubernetes.

Kubernetes-native workflow automation platform for complex, mission-critical data and ML processes at scale.

Durable execution layer for AI agents. Checkpoints, replay, resume, and observability primitives that make agent workflows persistent and replayable — no graph DSL required.

Machine Learning Pipelines for Kubeflow.

Build and manage real-life data science projects with ease!

The fastest way to build data pipelines. Develop iteratively, deploy anywhere.

The easiest way to automate your data.

An open-source unstructured data ETL tool to streamline the end-to-end unstructured data processing pipeline.

Enterprise-grade Voice AI simulation SDK for scenario-driven stress testing of multimodal and agentic systems.

Kubernetes-native Job Queueing.

A Highly Scalable Workload Manager.

A Cloud Native Batch System (Project under CNCF).

Light-weight, universal resource scheduler for container orchestrator systems.

Open Source ML Model Versioning, Metadata, and Experiment Management

Docker for Your ML/DL Models Based on OCI Artifacts

Compiler technology to transform a valid Open Neural Network Exchange (ONNX) graph into code that implements the graph with minimum runtime support.

Accessible large language models via k-bit quantization for PyTorch.

Open deep learning compiler stack for cpu, gpu and specialized accelerators

octoml-profile is a python library and cloud service designed to provide the simplest experience for assessing and optimizing the performance of PyTorch models on cloud hardware with state-of-the-art ML acceleration technology.

a high-performance, high-precision CPU, GPU, and memory profiler for Python

a platform for Neural Network Search (NAS) that allows you to generate efficient deep networks for your applications.

A framework to find the best performing AI/ML model for any AI problem.

An autoML framework & toolkit for machine learning on graphs

Provide an input CSV and a target field to predict, generate a model + code to run it.

AutoML library for deep learning.

Automatic architecture search and hyperparameter optimization for PyTorch.

an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.

An open source python library for scalable Bayesian optimisation.

a basic proof of concept for genetic architecture search in Keras.

An open source python library for AutoML.