From the course: Build an AI Application with React and AWS SageMaker

Basics of machine learning

From the course: Build an AI Application with React and AWS SageMaker

Start my 1-month free trial Buy for my team

Basics of machine learning

“

- [Presenter] Machine learning is a subset of artificial intelligence that enables computers to learn from data, identify patterns, and make decisions with minimal human intervention. From voice assistance to self-driving cars, machine learning is everywhere. The concept of machine learning has been around since the mid 20th century, involving from simple pattern recognition to complex algorithms capable of learning and adapting. There are three primary types of machine learning: supervised learning, where the model learns from labeled data; unsupervised learning where it discovers patterns in unlabeled data; and reinforcement learning where it learns by trial and error to achieve a specific goal. For example, we'll use to provide learning in this course. The machine learning process involves several steps: collecting data, preparing that data, choosing a model, training the model, evaluating its performance, and then tuning and deploying it. We'll do all these steps in this course. In short, these are the basics of machine learning, and we'll explore all these elements as we go through the course and build a project.

Contents