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Docker End to End Implementation

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Overview

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Dive into a comprehensive tutorial series on Docker implementation, covering essential topics from the fundamentals to advanced deployment strategies in machine learning. Learn why Docker is crucial, understand containerization concepts, and explore virtualization in ML. Build a Flask app for bank note authentication, deploy ML models using Flask and Flasgger, and master Docker installation across various operating systems. Gain proficiency in Docker commands, write and run Docker images, and leverage StreamLit for model deployment. Conclude with insights on deploying ML pipelines using Docker and Kubernetes, equipping you with end-to-end Docker expertise for data science and machine learning applications.

Syllabus

Docker Tutorial 1- Why and What is Docker, Dockers Containers, Virtualization In Machine Learning.
Docker Tutorial 2- Building A Flask App For A Bank Note Authentication.
Docker Tutorial 3-Deploying Machine Learning Models Using Flask And Flasgger.
Docker Tutorial 4-Docker Installation instructions In Windows And Other OS | Machine Learning.
Docker Tutorial 5- Understanding Docker Commands- Machine Learning.
Docker Tutorial 6- Writing, Building And Running Docker Image| Machine Learning.
Deploy Machine Learning Models Using StreamLit Library- Data Science.
Deployment Of Machine Learning PIPELINES Using Dockers and Kubernetes.

Taught by

Krish Naik

Reviews

5.0 rating, based on 1 Class Central review

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  • Profile image for Abdul Ahad
    Abdul Ahad
    Greatly explained, I am a beginner with Kubernetes, and I still have a good picture of how the app is deployed and exposed to the internet. However, I wanted to learn more about the scalability and a more physical explanation of how the scalability is actually happening with lots of containers.

    Overall, a good experience.
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