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Pipelines
来源:谷歌
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2020-04-19 10:04:08
Pipelines
Pipelines
Pipelines
ML Pipelines in Kubeflow
Pipelines
Introduction to Kubeflow Pipelines
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About
Kubeflow
Contributing to Kubeflow
Community
Events Calendar
Docs
Style Guide for the Kubeflow Docs
Getting Started
Kubeflow Overview
Installing Kubeflow
Cloud Installation
AWS for Kubeflow
Azure for Kubeflow
Google Cloud for Kubeflow
IBM Cloud Private for Kubeflow
Kubernetes Installation
Overview of Deployment on Existing Clusters
Kubeflow Deployment with kfctl_k8s_istio
Multi-user, auth-enabled Kubeflow with kfctl_existing_arrikto
Workstation Installation
Kubeflow on Linux
Kubeflow on Windows
Kubeflow on macOS
Deploy using MiniKF on GCP
Jupyter Notebooks
Overview of Jupyter Notebooks in Kubeflow
Set Up Your Notebooks
Create a Custom Jupyter Image
Submit Kubernetes Resources
Build a Docker Image on GCP
Troubleshooting Guide
Pipelines
Pipelines Quickstart
Installing Pipelines
Installation Options for Kubeflow Pipelines
Pipelines Standalone Deployment
Understanding Pipelines
Overview of Kubeflow Pipelines
Introduction to the Pipelines Interfaces
Concepts
Pipeline
Component
Graph
Experiment
Run and Recurring Run
Run Trigger
Step
Output Artifact
Building Pipelines with the SDK
Introduction to the Pipelines SDK
Install the Kubeflow Pipelines SDK
Build Components and Pipelines
Create Reusable Components
Build Lightweight Python Components
Best Practices for Designing Components
Pipeline Parameters
Python Based Visualizations
Visualize Results in the Pipelines UI
Pipeline Metrics
DSL Static Type Checking
DSL Recursion
GCP-specific Uses of the SDK
Manipulate Kubernetes Resources as Part of a Pipeline
Upgrading and Reinstalling
Samples and Tutorials
Experiment with the Pipelines Samples
Run a Cloud-specific Pipelines Tutorial
Reference
Component Specification
Pipelines API Reference
Pipelines SDK Reference
Fairing
Overview of Kubeflow Fairing
Install Kubeflow Fairing
Configure Kubeflow Fairing
Fairing on Azure
Fairing on GCP
Configure Kubeflow Fairing with Access to GCP
GCP Samples and Tutorials
Train and Deploy on GCP from a Local Notebook
Train and Deploy on GCP from a Kubeflow Notebook
Tutorials
Other Samples and Tutorials
Reference
Kubeflow Fairing SDK Reference
Kubeflow on AWS
Deployment
Install Kubeflow
Uninstall Kubeflow
Customizing Kubeflow on AWS
Logging
Private Access
Authentication and TLS Support
Storage Options
Troubleshooting Deployments on Amazon EKS
Kubeflow on AWS Features
Kubeflow on Azure
Deployment
Install Kubeflow
Initial cluster setup for existing cluster
Uninstall Kubeflow
End-to-End Pipeline Example on Azure
Access Control for Azure Deployment
Troubleshooting Deployments on Azure AKS
Kubeflow on GCP
Deploying Kubeflow
Set up a GCP Project
Set up OAuth for Cloud IAP
Deploy using UI
Deploy using CLI
Monitor Cloud IAP Setup
Delete using CLI
Delete using GCP Console
Features of Kubeflow on GCP
Pipelines on GCP
Authenticating Pipelines to GCP
Upgrading and Reinstalling
Enabling GPU and TPU
Using Preemptible VMs and GPUs on GCP
Pipelines End-to-end on GCP
Customizing Kubeflow on GKE
Using Your Own Domain
Authenticating Kubeflow to GCP
Using Cloud Filestore
Securing Your Clusters
Troubleshooting Deployments on GKE
End-to-end Kubeflow on GCP
Logging and monitoring
Components of Kubeflow
Jupyter Notebooks
Central Dashboard
Central Dashboard
Registration Flow
Hyperparameter Tuning
Introduction to Katib
Getting started with Katib
Running an experiment
Pipelines
Pipelines
Serving
Overview
KFServing
Seldon Serving
NVIDIA TensorRT Inference Server
TensorFlow Serving
TensorFlow Batch Predict
PyTorch Serving
Training
Chainer Training
MPI Training
MXNet Training
PyTorch Training
TensorFlow Training (TFJob)
Miscellaneous
Metadata
Nuclio functions
Tutorials, Samples, and Shared Resources
Kubeflow Samples
Codelabs, Workshops, and Tutorials
Blog Posts
Videos
Shared Resources and Components
Further Setup and Troubleshooting
Accessing Kubeflow UIs
Virtual Developer Environments
Microk8s for Kubeflow
MiniKF
Minikube for Kubeflow
Configuring Kubeflow with kfctl and kustomize
Kubeflow On-prem in a Multi-node Kubernetes Cluster
Usage Reporting
Multi-user Isolation
Job Scheduling
Troubleshooting
Upgrading Kubeflow
Upgrading a Kubeflow Deployment
Reference
Reference Overview
Dockerfile Locations
Katib Reference
Katib v1alpha3
Katib
Metadata Reference
Metadata API Reference
Kubeflow Metadata SDK Reference
PyTorchJob Reference
PyTorchJob v1
PyTorchJob
PyTorchJob v1beta2
PyTorchJob
TFJob Reference
TFJob v1
TFJob Common
TFJob TensorFlow
TFJob v1beta2
TFJob Common
TFJob TensorFlow
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