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Kubeflow Bootcamp - nieriorefasow63 - 06-15-2023
![[Image: b37i6e-CXTXb-EA4c-XDMs-XI0-HZyu9-Zr18-Z.jpg]](https://i.postimg.cc/TwBzqwMf/b37i6e-CXTXb-EA4c-XDMs-XI0-HZyu9-Zr18-Z.jpg)
Kubeflow Bootcamp
Published 6/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.49 GB | Duration: 7h 21m
Learn how to use Kubeflow for Machine Learning at scale on Google Cloud!
What you'll learn
Understand the core concepts of Kubeflow and its role in building scalable and portable machine learning workflows on Google Cloud.
Learn to deploy and manage Kubeflow pipelines to automate end-to-end machine learning workflows on Google Cloud.
Gain proficiency in utilizing Kubeflow components
Develop skills in leveraging Google Cloud's AI Platform for training and serving machine learning models within the Kubeflow environment.
Explore the integration of Kubeflow with other Google Cloud services
Master the use of Kubeflow's monitoring and logging capabilities to ensure effective tracking and debugging of machine learning workflows.
Learn best practices for scaling and optimizing machine learning workloads using Kubeflow on Google Cloud
Understand security and governance considerations when working with Kubeflow on Google Cloud
Requirements
Understanding of general Cloud Service Providers (we provide a Google Cloud intro)
Understand general machine learning concepts
Permissions to subscribe to Google Cloud (credit card may be required)
Some Python Programming Experience
Description
Unlock the Power of Machine Learning Workflows on Google Cloud with Kubeflow!Supercharge your data science skills and revolutionize your machine learning workflows with our comprehensive Udemy course on Kubeflow on Google Cloud. Dive into the world of scalable and portable ML pipelines with this step-by-step guide to harnessing the full potential of Kubeflow.Master the art of automating end-to-end machine learning workflows using Kubeflow and discover how it seamlessly integrates with the robust infrastructure of Google Cloud. Whether you're a data scientist, ML engineer, or aspiring AI enthusiast, this course equips you with the knowledge and hands-on experience to take your projects to new heights.What you'll learn:Unleash the true potential of Kubeflow by understanding its core concepts and its role in building scalable ML workflows.Deploy and manage Kubeflow pipelines effortlessly to automate and streamline your ML projects on Google Cloud.Harness the power of Kubeflow's components, including Katib and Argo, to optimize hyperparameter tuning and workflow orchestration.Maximize the potential of Google Cloud's AI Platform for efficient model training and deployment within the Kubeflow ecosystem.Integrate Kubeflow seamlessly with other Google Cloud services like BigQuery and Cloud Storage for enhanced data processing and storage.Master the art of monitoring and logging in Kubeflow to ensure the success of your ML projects with real-time insights and debugging capabilities.Scale and optimize your ML workloads effectively using Kubeflow, leveraging distributed training and resource allocation techniques.Embrace best practices in security and governance, ensuring compliance and data privacy when working with Kubeflow on Google Cloud.Don't miss out on this opportunity to become a Kubeflow expert and accelerate your career in the rapidly evolving field of AI and ML. Enroll now and unlock the full potential of Kubeflow on Google Cloud with our comprehensive Udemy course!
Overview
Section 1: Course Introduction
Lecture 1 FAQ AND COURSE DOWNLOADS
Lecture 2 Course Overview
Section 2: Google Cloud Overview and Setup
Lecture 3 Overview of Google Cloud Section
Lecture 4 What is Cloud? A Cloud Computing Overview
Lecture 5 GCP Network Infrastructure
Lecture 6 GCP Network Connections
Lecture 7 Why Choose GCP?
Lecture 8 Google Cloud Account Set-Up
Lecture 9 Billing and Budgets
Lecture 10 Billing Tour: DEMO
Lecture 11 Setting a Budget Alert: DEMO
Lecture 12 Google Cloud Storage Options
Lecture 13 Cloud Storage Overview
Lecture 14 Cloud Storage DEMO
Section 3: Kubernetes Overview
Lecture 15 Introduction to Kubernetes Section
Lecture 16 Kubernetes Basics Overview
Lecture 17 Understanding Containers
Lecture 18 Understanding Nodes and Control Plane
Lecture 19 Understanding Kubernetes API
Lecture 20 Container Images
Lecture 21 Cloud Build DEMO
Lecture 22 Google Kubernetes Engine - GKE
Lecture 23 Kubernetes Architecture
Lecture 24 GKE via GUI DEMO
Lecture 25 Kubectl
Lecture 26 GKE via Command Line - DEMO
Lecture 27 Kubernetes Deployments
Lecture 28 Kubernetes Deployment Updates
Lecture 29 Kubernetes Deployment Strategies
Lecture 30 Kubernetes Deployment - DEMO
Lecture 31 Kubernetes Pod Networking
Lecture 32 Kubernetes Storage with Volumes
Lecture 33 Volume Storage - DEMO
Section 4: Understanding Machine Learning Fundamentals
Lecture 34 Introduction to Machine Learning Fundamentals
Lecture 35 Machine Learning Pathway
Lecture 36 Why Machine Learning?
Lecture 37 Types of Machine Learning Algorithms
Lecture 38 Supervised Learning Process
Lecture 39 AI vs ML
Lecture 40 AI and ML on Google Cloud
Lecture 41 Vertex AI Overview
Lecture 42 Vertex AI Workbench: Notebooks in the Cloud
Section 5: Kubeflow Pipelines with Google Cloud
Lecture 43 Kubeflow Section Overview
Lecture 44 Vertex AI Pipelines
Lecture 45 Vertex AI Pipelines and SDKs
Lecture 46 AI Pipeline via Notebook DEMO
Lecture 47 Kubeflow Overview
Lecture 48 Kubeflow DSL
Lecture 49 Kubeflow Pre-Built Components
Lecture 50 Kubeflow Python Components
Lecture 51 Kubeflow Custom Components
Lecture 52 Kubeflow Compilation
Cloud Developers interested in using Kubeflow on Google Cloud
HOMEPAGE
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