Want to make your Machine Learning projects portfolio-ready? In this video, we’ll show you how to version-control your ML cloud deployment with GitHub covering project structuring, commit practices, branching, and how to push your deployment-ready model code to GitHub like a professional.
Perfect for:
Data Science & AI learners
Job seekers building a portfolio
Professionals deploying ML apps on cloud
👉 Key Takeaways:
Why GitHub matters for ML projects and career growth
Best practices for ML version control
Step-by-step GitHub push workflow
How clean GitHub repos can boost your hiring visibility
🌐 Explore structured programs that accelerate your career in Data Science & AI with hands-on projects and 100% job assurance:
Be the first to comment