Introduction

Completed

Azure Machine Learning is a cloud-based environment where you can build and manage machine learning models. It’s designed to govern the entire ML life cycle, so you can train and deploy models without focusing on setup. The platform is suitable for any kind of machine learning, from classical to deep learning, to supervised and unsupervised learning.

Azure Machine Learning is structured to help teams of data scientists and ML engineers make the most of their existing data processing and model development skills. Whether you use Python or R—or have previous experience with other open-source platforms such as PyTorch and TensorFlow—Azure Machine Learning is flexible enough to support these platforms and accelerate your work.

With in-built services, like Azure Machine Learning studio that provides a user-friendly interface, and Automated Machine Learning capabilities that assist you in model selection and training—Azure Machine Learning has tools and features to suit every level of experience.

Prerequisites

  • Familiarity with machine learning models and terms

Learning objectives

In this module, you will:

  • Assess the benefits of Azure Machine Learning
  • Describe what Azure Machine Learning is
  • Define scenarios where Azure Machine Learning can be applied