How to Create & Use Python Virtual Environments | ML Project Setup + GitHub Actions CI/CD

🚀 Learn how to create and use a virtual environment in Python, set up a complete Python virtual environment, and structure a professional Machine Learning project! In this step-by-step guide, we will cover:

✅ Setting Up VS Code for ML Development
✅ Creating and Managing a Virtual Environment
✅ Organizing Your ML Project (API, Dashboard, Scripts, Tests)
✅ Setting Up Git and Pushing to GitHub
✅ Automating CI/CD with GitHub Actions

By the end of this tutorial, you will have a fully structured ML project with best practices in virtual environments, GitHub workflows, and deployment automation. Perfect for ML Engineers, AI Developers, and Data Scientists! 🎯

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📌 Chapters:
0:00 - Introduction
0:30 What is the virtual environment?
1:26 - Setting Up VS Code for ML Development
1:52 - Creating a workspace on VS Code
2:33- Creating a Virtual Environment (Step by Step)
5:30 - Structuring the ML Project
4:35 - Setting up project structure
12:17 - Initializing Git & Pushing to GitHub
13:56 - CI/CD Setup with GitHub Actions

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[AhsanKhan-rzgl]

Thanks for this detailed and informative video. Can you provide a Git link to this template, so that all of us could use it in our projects?