Training and deploying ML models in azure ml service

Ayeshmantha Perera
Jun 6 · 2 min read

Today will be focusing about one of machine learning capability azure have provided in order to train your own models using most of the popular machine learning frameworks and deploying them inside docker containers in order to expose your models for serving.

What is Azure Machine Learning service?

Process inside Azure ml service.

With Azure machine Learning service you can develop train test deploy manage and track you’re machine learning model.It supports almost all open source machine learning frameworks and python packages which will be useful on the pipeline of machine learning model building.It Supports rich tools like Jupyter notebooks or the Azure Machine Learning for Visual Studio Code extension. Azure Machine Learning service also includes features that automate model generation and tuning to help you create models with ease, efficiency, and accuracy.

You can train you’re models locally or even on cloud with the compute instances and environments provided by azure.For example Azure Machine Learning Compute and Azure Databricks, and with advanced hyperparameter tuning services, you can build better models faster by using the power of the cloud.

How is Azure Machine Learning service different from Machine Learning Studio?

In the next blog will be having a look at a real world scenario on training a model with azure ml service.