37 How to Create a job with Python SDK v2 Step by Step Guide

#AzureML #AzureMachineLearning #PythonSDK
Unlock the power of automation and streamline your machine learning workflows with Azure ML and the Python SDK v2! In this comprehensive tutorial, you’ll learn how to train a machine learning model in Azure ML using Python, step-by-step. Whether you’re a data scientist, ML engineer, or developer, this guide will help you efficiently manage compute resources, submit training jobs, and monitor them in real-time-all through Python code.
🎯 What you’ll learn in this video:
Setting up and authenticating with Azure ML Workspace using Python SDK v2.
Configuring compute clusters for scalable training.
Creating and submitting training jobs with YAML files.
Monitoring job status and retrieving trained models for deployment.
✨ Key Highlights:
Practical examples to set up your workspace programmatically.
Real-world use cases for Python SDK v2 in model training.
Troubleshooting tips for common errors during the training process.
📌 Who is this video for?
Machine Learning Engineers looking to automate training pipelines.
Data Scientists eager to integrate Python scripts into Azure ML workflows.
Developers interested in the seamless integration of ML into CI/CD pipelines.
🔗 Resources Covered:
Code: [github.com/Dee...]
Azure Machine Learning (DP-100) Playlist: [ • Azure ml ]
Azure DevOps Playlist: [ • azure devops ]
Follow Me for More Content:
Medium: [ / deepp.knowledge ]
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