Machine Learning & LLMs
Machine learning, neural networks and large language models (LLMs) are important components of modern AI systems. Learn about popular machine learning paradigms for classification, regression, clustering and anomaly detection with the help of fully automated and customizable functions that handle 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 neural net framework. Make use of Chat Notebooks as well as powerful built-in functions for calling LLM functionality and allowing LLMs to access Wolfram Language tools.
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.
Upcoming Events
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OCT 16 | Online
Introduction to Machine Learning in Wolfram Language
Gain experience using machine learning superfunctions available in Wolfram Language. 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.
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OCT 23 | 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. Learn about the Neural Net Repository and transfer learning, as well as how to train, test and look inside a neural net. Earn a certificate of course completion.
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OCT 27–31 | Online
Daily Study Group: Neural Networks for AI
Perfect for anyone new to AI or those looking to further their understanding, this Daily Study Group provides an introduction to neural networks and their application in AI using Wolfram Language. Explore fundamental concepts such as embeddings, network architecture and training processes, and gain hands-on experience with the Wolfram Neural Net Framework.
