ML

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. [...]

There are numerous types of machine learning algorithms, each of which has certain characteristics that might make it more or less suitable for solving a particular problem. Decision trees and support-vector machines (SVMs) are two examples of algorithms that can both solve regression and classification problems, but which have [...]

Machine learning is not just a single task or even a small group of tasks; it is an entire process, one that practitioners must follow from beginning to end. It is this process—also called a workflow—that enables the organization to get the most useful results out of their machine [...]

Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This is the first of four courses [...]

In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, [...]

Like most subjects, practice makes perfect in Data Science. In the capstone project, you will apply the skills learned across courses in the Practical Data Science with MATLAB specialization to explore, process, analyze, and model data. You will choose your own pathway to answer key [...]