# 모두를 위한 MLOps 튜토리얼 (한국어)

> Clean Markdown view of GeekNews topic #5675. Use the original source for factual precision when an external source URL is present.

## Metadata

- GeekNews HTML: [https://news.hada.io/topic?id=5675](https://news.hada.io/topic?id=5675)
- GeekNews Markdown: [https://news.hada.io/topic/5675.md](https://news.hada.io/topic/5675.md)
- Type: news
- Author: [xguru](https://news.hada.io/@xguru)
- Published: 2022-01-04T09:50:04+09:00
- Updated: 2022-01-04T09:50:04+09:00
- Original source: [mlops-for-all.github.io](https://mlops-for-all.github.io/)
- Points: 29
- Comments: 0

## Topic Body

- MLOps를 공부하려고 하지만 어떻게 시작해야 하는지 모르는 분들을 위한 지침서

- 오픈소스(MIT) 문서로 누구나 참여 가능

Introduction

1. What is MLOps?

2. Components of MLOps

3. Why Kubernetes?

Setup Kubernetes

1. Introduction

2. Setup Kubernetes

3. Install Prerequisite

4.1. Install Kubernetes - K3s

4.2. Install Kubernetes - Minikube

4.3. Install Kubernetes - Kubeadm

5. Install Kubernetes Modules

6. (Optional) Setup GPU

Setup Components

1. Kubeflow

2. MLflow Tracking Server

3. Seldon-Core

4. Prometheus & Grafana

Kubeflow UI Guide

1. Central Dashboard

2. Notebooks

3. Tensorboards

4. Volumes

5. Experiments(AutoML)

6. Kubeflow Pipeline 관련

Kubeflow

1. Kubeflow Introduction

2. Kubeflow Concepts

3. Install Requirements

4. Component - Write

5. Pipeline - Write

6. Pipeline - Upload

7. Pipeline - Run

8. Component - InputPath/OutputPath

9. Component - Environment

10. Pipeline - Setting

11. Pipeline - Run Result

12. Component - MLFlow

13. Component - Debugging

API Deployment

1. What is API Deployment?

2. Deploy SeldonDeployment

3. Seldon Monitoring

4. Seldon Fields

5. Model from MLflow

6. Multi Models

- 다루지 못한 것들

- Python 가상환경 설치

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