Building End-to-end Machine Learning Workflows with Kubeflow 1

سرفصل های دوره

In this course, you will learn how to effectively build end-to-end scalable, production grade machine learning workflows using Kubeflow.

1. Course Overview

1. Course Overview

2. Introduction

1. Version Check

2. Course Introduction

3. Kubeflow Overview

4. Course Structure

5. Fashion-MNIST Use Case Overview

3. Setting up Kubeflow Environment

1. Introduction

2. Overview

3. Kubeflow Deployment Options

4. Setup Kubeflow on GCP

5. Demo - Setup Kubeflow Prerequisites

6. Demo - Setup OAuth for GCP Cloud IAP

7. Demo - Setup Kubeflow on GCP

8. Demo - Clean Kubeflow Environment on GCP

9. Summary

04. Exploring Kubeflow Components

01. Introduction

02. Overview

03. Docker Introduction

04. Demo - Docker Overview

05. Why Kubernetes

06. Kubernetes Introduction

07. Kubernetes Core Components

08. Demo - Kubernetes Overview (Part 1)

09. Demo - Kubeflow Overview (Part 2)

10. Demo - Kubeflow Central Dashboard Overview

11. Summary

05. Building Machine Learning Model on Kubeflow

01. Introduction

02. Overview

03. Model Development Process and Challenges

04. Kubeflow Components for Training

05. Fashion-MNIST Training Workflow

06. Kubeflow Notebook

07. Demo - Setting up Notebook Server with a Pre-built Image

08. Demo - Setting up Notebook Server with a Custom Image

09. Deep Learning Model Overview for Fashion-MNIST

10. Demo - Training in Kubeflow Notebook

11. Metadata Overview

12. Demo - Metadata Tracking

13. Kubeflow Fairing Overview

14. Demo - Kubeflow Fairing

15. Distributed Training

16. Demo - Distributed Training with GPU

17. Demo - Distributed Training with TFJob

18. Hyperparameter Tuning with Katib

19. Demo - Performing Hyperparameter Tuning with Katib

20. Summary

06. Serving Machine Learning Model on Kubeflow

01. Introduction

02. Overview

03. Model Serving Process and Challenges

04. Kubeflow Components for Serving

05. KFServing Overview

06. Demo - Serving Model Using KFServing

07. Demo - Pre and Post-processing Using KFServing

08. Canary Rollout Overview

09. Demo - Canary Rollout Using KFServing

10. Demo - Performance Monitoring Using KFServing, Prometheus, and

11. Demo - Auto Scaling and Load Testing

12. Summary

07. Build Machine Learning Pipeline Using Kubeflow Pipeline

01. Introduction

02. Overview

03. Machine Learning Workflow Pipeline and Challenges

04. Kubeflow Components for Building Pipeline

05. Kubeflow Pipeline Overview

06. Fashion-MNIST Use Case Pipeline

07. Demo - Building Kubeflow Pipeline with Hyperparam

08. Demo - Adding Training Step to Kubeflow Pipeline

09. Demo - Adding Serving Step to Kubeflow Pipeline

10. Demo - Building Kubeflow Pipeline from Notebook

11. Summary

8. Whats Next

1. Introduction

2. Extend Your Kubeflow Journey

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تولید کننده: PluralSight