When I started learning AzureML, I followed Microsoft's official tutorials, but I quickly realized I wanted more flexibility with PyTorch—especially for working with a wider range of datasets and models. However, I struggled to find a clear, beginner-friendly tutorial for deploying PyTorch (including Torchvision) models on AzureML. Since nothing quite fits my needs, I decided to create this repository—a collection of well-documented, easy-to-follow notebook tutorials.
This project covers everything needed to deploy a PyTorch model on AzureML, from training to deployment and inference. The tutorials break down the key concepts, making them easy to understand while encouraging hands-on experimentation. Whether you're a beginner exploring ML model deployment or an experienced user looking for a streamlined PyTorch-to-AzureML workflow, this repo has you covered! 🚀
Start here: PyTorch_AzureML.ipynb
💡 This is an ongoing project! I’ll continue to add more tutorials, improvements, and best practices. Contributions, feedback, and suggestions are always welcome! Let me know if you’d like any refinements! 😊