Train a Machine Learning Model with Azure Machine Learning

In this article, I will tell you how you can train models in the cloud using Azure Machine Learning Studio.

Before you start reading, you can read my Azure Machine Learning Studio article on how to create Azure Machine Learning Studio and what steps you should follow before you start training when you create it.

What are the Advantages of Training a Machine Learning Model in the Cloud?

• The pay-per-use model of the cloud is good for AI or machine learning workloads.
• The cloud makes it easy for organizations to experiment with machine learning capabilities and scale up as projects go into production and demand grows.
• The cloud makes smart capabilities accessible without requiring advanced skills in artificial intelligence or data science.
• AWS, Microsoft Azure, and Google Cloud Platform offer many machine learning options that don’t require deep AI knowledge, machine learning theory, or a team of data scientists.

Model Training

With the Designer option in Azure Machine Learning Studio, users can create a pipeline with drag-and-drop method, allowing the steps from model creation to training.

In this article, I will tell you how you can train a model with Jupyter by using Azure Machine Learning Studio without using this option.