GitHub Repo: https://github.com/iQuantC/MLOps01
🚀 Description:
In this video, I’ll walk you through the complete process of building and deploying a Simple MLOps Project step-by-step. We’ll train a machine learning model, build it into a Flask application, and deploy it using a fully automated Jenkins CI/CD Pipeline.
🔑 What You'll Learn:
✅ Training a Machine Learning model and integrate it into a Flask web app.
✅ Setting up Jenkins in a container and creating a CI/CD pipeline for:
✅ Checking out code from GitHub.
✅ Linting and testing your code for quality assurance.
✅ Scanning your application for vulnerabilities.
✅ Building a Docker image for your app.
✅ Pushing the Docker image to DockerHub.
✅ Deploying the Docker image to Amazon ECS for production.
✅ Serving your model on an interactive web UI accessible via your browser.
👨💻 Demo Overview:
We’ll cover:
1️⃣ Training a simple machine learning model in Python.
2️⃣ Building a REST API using Flask to serve predictions.
3️⃣ Writing a Jenkinsfile to automate the CI/CD pipeline.
4️⃣ Setting up AWS ECS for hosting the application and configuring it for scale.
💡 Why Watch This Video?
✅ Learn end-to-end MLOps: from model training to production deployment.
✅ Understand CI/CD principles in a practical and real-world scenario.
✅ Get hands-on experience with Jenkins, Docker, Flask, and AWS ECS.
🚀 Timestamps:
0:00 Intro
1:16 ML Code Overview
5:56 Dockerfile
7:57 Test Cases
10:00 Set up Jenkins Container
12:38 Patch Jenkins Image for Docker-in-Docker (DinD) tasks
15:24 Run Jenkins DinD Container & access Jenkins UI on browser
19:40 Integrate Jenkins with GitHub
21:55 GitHub Code Checkout with Jenkinsfile
25:58 Linting the Codes
35:10 Testing the Code
35:37 Training the ML Model
37:22 Testing Code Continued
38:29 Trivy Filesystem Scan
42:08 Build Docker Image of ML Model App
48:00 Trivy Docker Image Scan
50:27 Push Image to DockerHub
1:01:24 Deploy ML Model to AWS ECS
1:11:12 Create Amazon ECS Task Role
1:19:43 ML Model Serving on Interactive UI
1:20:55 Automate ML App Deploy to AWS ECS with Jenkinsfile
1:24:04 Project Clean up
📂 Resources:
All the code, configurations, and scripts are available here: [https://github.com/iQuantC/MLOps01].
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#MLOps #CI/CD #Jenkins #AWS #MachineLearning #Docker #Flask
Disclaimer: Video is made for educational purposes
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Happy MLOps'ing! 🎉