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  • 2 days ago
Training a machine learning model is just the beginning. The real challenge? Preparing it for deployment in the cloud.

In this Masterclass, learn the essential steps to make your ML model robust, reproducible, and production-ready:

πŸ“Œ What You’ll Learn:

Model Validation & Final Testing: Cross-validation, overfitting checks, and stress-testing with unseen data

Code Clean-Up & Optimization: Refactor, log, version, and document your code

Environment Packaging: Export dependencies with Conda or pip; ensure reproducibility

Cloud Deployment Prep: Set up APIs, containers, and test on AWS, GCP, or Azure

🌟 Level Up Your Career in Data Science & AI

πŸŽ“ Postgraduate Program in Data Science & Analytics (PGA) – 6 months, 100% job assurance, 25+ projects, 10+ tools
πŸŽ“ Executive PG Program in Data Science & AI (EPGP-DSAI) – 11 months, 35+ projects, 2,500+ hiring partners, 52% average salary hike
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