Deploy Your ML Web App on AWS EC2: Step-by-Step Guide

https://bit.ly/4cB2kaK Built a machine learning model? Now let the world use it. Learn how to connect to AWS EC2 and deploy your ML web app—from setting up the instance to making your app live on the internet.

In this hands-on session, we walk you through everything you need to know to move from local development to full deployment in the cloud.

Timestamp ⏱️

00:00 – Check EC2 files & install WinSCP
02:21 – Connect WinSCP to EC2 using PPK key
04:39 – Upload deployment files to EC2
06:50 – Install Python & pip on EC2
09:16 – Troubleshoot Python dependency issues
11:37 – Manually install libraries & set up EC2 security
16:53 – Deploy and access ML web app via URL

🎓 What You’ll Learn:

1️⃣ Getting Started with EC2

🔹 Launching and configuring an EC2 instance

🔹 Securely connecting via SSH and understanding key pairs

2️⃣ Setting Up the Environment

🔹 Installing Python, Flask, and necessary ML libraries

🔹 Transferring code from local to EC2

3️⃣ Deploying the Web App

🔹 Running your Flask or Streamlit app

🔹 Setting up security groups and public access

🔹 Making your ML model available to real users
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📚 Recommended Reads:

📘 Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow – Aurélien Géron

📘 Flask Web Development – Miguel Grinberg

📘 Amazon Web Services in Action – Michael Wittig

🎬 Must-Watch Documentaries:

🎥 The Age of AI

🎥 The Cloud Revolution

🎥 Hello World: Deploying ML in Production
About Imarticus Learning

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