Choosing the Right Machine Learning Service in Azure (Part 1 of 4)

By Ashwin Venugopal -

 




To read part 2, please click here
To read part 3, please click here
To read part 4, please click here









Choosing an Azure Service for ML

Azure offers vast number of services, it often makes it difficult for someone new to Azure to select the right one for a specific task. Choosing the right service with the right layer of abstraction could save you months if not years of time to market your ML-based product or feature, while the wrong service may initially allow you to start producing results quickly, but, it will also make it impossible to improve the model performance for a specific domain or extend a model for other tasks.

What is the Azure Machine Learning Service?

The term Azure Machine Learning Service refers to the popular Azure service that offers capabilities in building custom ML solutions and contains various components to manage resources (like compute clusters and data storage) and assets (like datasets, experiments, models, pipelines, etc.), as well as access to these resources and assets, all within the same workspace.

The access to the other ML services (like Azure Automate Machine Learner, the Azure Machine Learning Design, etc.) sharing the same resources and assets through the ML workspace, is also offered by the Azure Machine Learning service. Due to this fact, it is also referred as the Azure Machine Learning service or the Azure Machine Learning workspace.

Managed ML Services

These type of services are generally easy to use, quick to embed into an application, and don't require any operational overhead making it the most suitable to create an AI-based application or feature without any training data, models, and operating model deployments in production. 

These services are used with pre-trained models that sometimes can be trained or fine-tuned for a specific application domain, however, if you use customized models, then, it will add to the benefits of managed services with the flexibility of custom application domain. Hence, we can further look into the Azure Cognitive Services, customizable AI services, and Azure Applied AI Services.  

 






To read part 2, please click here
To read part 3, please click here
To read part 4, please click here











































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