🚀 KServe & Kubeflow :- Build, Register, Deploy & Draw Predictions from Machine Learning Model 🚀 скачать в хорошем качестве

🚀 KServe & Kubeflow :- Build, Register, Deploy & Draw Predictions from Machine Learning Model 🚀

Support Us: https://buymeacoffee.com/iquantconsult GitHub Repo: https://github.com/iQuantC/Kubeflow-K... 💡Description: In this video, we’ll walk you through building a powerful machine learning model using Kubeflow and deploying it seamlessly to KServe with InferenceService! You’ll learn how to: ✅ Set up Kubeflow for end-to-end ML workflows ✅ Train your machine learning model ✅ Register your machine learning model to Amazon S3 Bucket ✅ Deploy the model to KServe for scalable, real-time inference ✅ Leverage InferenceService to manage and monitor your model Whether you're just getting started with MLOps or looking to enhance your skills, this tutorial is perfect for you! Don’t forget to like, subscribe, and hit the notification bell for more DevOps and MLOps content from iQuant! 🎉 #Kubeflow #KServe #MLOps #MachineLearning #DevOps #iQuant #InferenceService Timestamps: 0:00 - Introduction 1:34 - Code Overview 6:15 - Set Up AWS Resources 16:06 - Set Up Minikube Kubernetes Cluster 17:47 - Create AWS IAM User with S3 Access 20:55 - Install AWS CLI 24:40 - Install Kubeflow and kfp SDK 26:42 - Access Kubeflow UI via port-forwarding and ssh tunneling 29:42 - Generate YAML Script and Build Kubeflow Pipeline 35:00 - Install and Set Up KServe 38:02 - Inference Service & Prediction with ML Model 45:17 - How to use Custom DNS 49:38. - Clean Up Disclaimer: This video is for educational purposes only. The tools and technologies demonstrated are subject to change, and viewers are encouraged to refer to the official documentation for the most up-to-date information. Thank you for watching! 🎉