Explore the fundamentals behind machine learning, focusing on unsupervised and supervised learning. You’ll learn what each approach is, and you’ll see the differences between them. In addition, you’ll explore common machine learning techniques including clustering, classification, and regression. Lastly, you’ll walk through an example machine learning workflow that outlines key decision points in the process.
Part 1: Machine Learning Fundamentals Explore the fundamentals behind machine learning, focusing on unsupervised and supervised learning. Learn about the common techniques, including clustering, classification, and regression.
Part 2: Unsupervised Machine Learning Get an overview of unsupervised machine learning, which looks for patterns in datasets that don’t have labeled responses. This approach lets you explore your data when you’re not sure what information the data contains.
Part 3: Supervised Machine Learning Learn how to use supervised machine learning to train a model to map inputs to outputs and predict the response for new inputs.
Part 4: Getting Started with Machine Learning Walk through a machine learning workflow step by step, and get insight into several key decision points along the way. The example workflow shows how to use machine learning to develop a cell phone health-monitoring app.