Machine Learning Toolkit for Kubernetes
PipelineAI Kubeflow Distribution
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
Machine Learning Pipelines for Kubeflow
Standardized Serverless ML Inference Platform on Kubernetes
Elyra extends JupyterLab with an AI centric approach.
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
Kubeflow’s superfood for Data Scientists
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)
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.
DoEKS is a tool to build, deploy and scale Data Platforms on Amazon EKS
Distributed Machine Learning Patterns (Manning Publications). Now available for early access. Read it online for free! https://bit.ly/2RKv8Zo
Example for end-to-end machine learning on Kubernetes using Kubeflow and Seldon Core
Kubernetes Guide. Learn all about Kubernetes monitoring, networking, and containers.
Train and Deploy Machine Learning Models on Kubernetes using Amazon EKS
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