Machine Learning Toolkit for Kubernetes

A guideline for building practical production-level deep learning systems to be deployed in real world applications.

PipelineAI

Machine Learning Pipelines for Kubeflow

Standardized Serverless ML Inference Platform on Kubernetes

cube studio开源云原生一站式机器学习/深度学习AI平台，支持sso登录，多租户/多项目组，大数据平台对接，notebook在线开发，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务VGPU，边缘计算，serverless，标注平台，自动化标注，数据集管理，大模型微调，vllm大模型推理，llmops，私有知识库，AI模型应用商店，支持模型一键开发/推理/微调，支持国产cpu/gpu/npu芯片，支持RDMA，支持pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/spark/ray/volcano分布式

Elyra extends JupyterLab with an AI centric approach.

Distributed ML Training and Fine-Tuning on Kubernetes

Automated Machine Learning on Kubernetes

Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.

A CLI for Kubeflow.

Kubeflow’s superfood for Data Scientists

DoEKS is a tool to build, deploy and scale Data & ML Platforms on Amazon EKS

Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo

👩‍🔬 Train and Serve TensorFlow Models at Scale with Kubernetes and Kubeflow on Azure

deployKF builds machine learning platforms on Kubernetes. We combine the best of Kubeflow, Airflow†, and MLflow† into a complete platform.

Helmut Hoffer von Ankershoffen experimenting with arm64 based NVIDIA Jetson (Nano and AGX Xavier) edge devices running Kubernetes (K8s) for machine learning (ML) including Jupyter Notebooks, TensorFlow Training and TensorFlow Serving using CUDA for smart IoT.

A personal research and development (R&D) lab that facilitates the sharing of knowledge.