This course introduces the easy-to-use machine learning superfunctions available in Wolfram Language. You will learn how to perform supervised and unsupervised learning tasks with just a few lines of code. We will start with regression, classification, clustering and anomaly detection, and from there, we'll move on to the state-of-the-art neural network framework. Examples using the Wolfram Neural Net Repository are shown with instructions for building your own neural networks from scratch. Basic familiarity with Wolfram Language or introductory-level skill in any programming language is recommended. A certificate of course completion is available.
Learn more about this course by going to the Wolfram U catalog