Learn about popular machine learning paradigms for classification, regression, clustering and anomaly detection as well as the usefulness of an automated framework that handles everything from feature extraction to performance evaluation. See how you can select pre-trained neural net models from a repository to apply to your own data, customize existing models or build models from scratch with the help of a symbolic framework.
These courses cover many different topics, starting with introductory machine learning concepts and Wolfram Language built-in functions and diving into the complexities of building and training neural networks. Earn course completion certificates and prepare for Wolfram Language Level 1 certification.
Mar 19 | Online
Introduction to Machine Learning in Wolfram Language
Gain experience using machine learning superfunctions available in Wolfram Language’s neural network framework. This course demonstrates how to perform supervised and unsupervised machine learning tasks and also covers regression, classification, clustering and anomaly detection. Earn a certificate of course completion.See Details and Register
Mar 21 | Online
Introduction to Neural Networks in Wolfram Language
This course provides an introduction to the state-of-the-art Neural Net Framework in Wolfram Language. You will learn how to explore the Wolfram Neural Net Repository for pre-built and pre-trained models and how to apply them to your own dataset.See Details and Register
Mar 25–29 | Online
Daily Study Group: Wolfram Tools for LLMs
This study group brings you up to speed on the latest tools and devotes daily sessions to using the newly expanded Wolfram GPT, Chat Notebooks, functions to connect to LLMs and built-in AI-related functionality in Wolfram Language.