Azure AI Fundamentals (AI-900) Study Guide

Chapter 4. Fundamental Principles of Machine Learning

In the AI-900 exam, about 20%–25% of the material covers the core principles of ML on Microsoft Azure. This includes foundational techniques like regression analysis, classification, and clustering. Each of these techniques offers a unique approach to problem solving. They allow you to select the right method based on the data type and the predictions you need to make. In this chapter, we’re going to dig into these must-know concepts and services. Understanding these ideas will help you tackle questions on the AI-900 exam, so you’ll know not only what these services are but also how they work and why they matter.

What Is Machine Learning?

ML, which is a branch of AI, allows systems to perform tasks like data analysis without needing explicit instructions. Instead, it processes large amounts of historical data, identifies patterns, and makes predictions based on those patterns. For instance, you can use ML to classify images, numbers, or documents and make predictions from them.

Let’s say you work for a financial services organization looking to differentiate between fraudulent and genuine transactions. With ML, the system would learn to identify patterns from known examples and then apply that knowledge to predict whether a new transaction is genuine.

ML is essential for modern businesses because it helps automate data collection, classification, and analysis. This speeds up decision making and drives growth. It improves processes ...