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Kubernetes for MLOps: A Beginner-Friendly Guide

Welcome to the Kubernetes for MLOps tutorial! This repository contains detailed notes, practical examples, and code to help you master Kubernetes fundamentals, distributed computing, microservices, and their applications in the world of Machine Learning Operations (MLOps).


What You'll Learn

In this tutorial, we’ll cover:

  1. Distributed Computing Fundamentals

    • Clusters, Lead Nodes, Communication, and Concurrency.
    • Comparison with frameworks like Apache Spark.
  2. Kubernetes Internals

    • Master Node and Worker Node Architecture.
    • Key components like API Server, etcd, kubelet, and kube-proxy.
  3. Microservices for MLOps

    • Microservices explained with a real-world Machine Learning scenario.
    • How Docker and Kubernetes revolutionize microservices deployment for ML workflows.

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Contains entire fundamentals for Distributed Computing, Microservices and Kubernetes

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