What you'll learn:
- How to use Azure Machine Learning from Development to Production
- How to Use Azure DevOps for Continuous Integration, continuous deployment on Machine Learning
- How to automate End 2 End machine Learning Solution on Azure
- How to Deploy Machine learning Models on Azure (Azure Container Instances, Azure Kubernetese Services, managed endpoints)
- Run an end-to-end CI/CD MLOps pipeline using Azure DevOps & Azure Machine learning
- Bests practices and highly demanded capabilities of machine learning on Azure Cloud
Acourse instructed by me and my digital twin if:
You are looking for a comprehensive, engaging, and fun course for mastering Azure Machine learning ( up to even advanced industry-required topics) plus fully hands-on end-to-end implantation of MLOps ( DevOps for Machine learning on Azure). If yes, then this is the right and very unique course for you!
Machine Learning Operations (MLOps) is a rapidly growing culture nad highly demanded in the industry with a set of principles, and guidelines defined in the machine learning world to deploy a machine learning model into production.
Azure Machine Learning is a cloud service for accelerating and managing the machine learning project lifecycle. Machine learning professionals, data scientists, and engineers can use it in their day-to-day workflows: Train and deploy models, and manage MLOps.
You can create a model in Azure Machine Learning or use a model built from an open-source platform, such as Pytorch, TensorFlow, or scikit-learn. MLOps tools help you monitor, retrain, and redeploy models.
Key points about this course
Very detailed in-depth and comprehensive coverage
This course will help you prepare for entry into this hot career path of Machine Learning and MLOps
The course is regularly updated with recent features
Best practices and impactful features of Azure ML (e.g, Explainable AI) with its tricks are all covered
Contains some extra videos relevant to Azure Machine Learning and Databricks (Apache Spark)
