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
-
May 20 | Online
Injecting Reliability into Generative AI
This talk explains the problems that large language models (LLMs) have with reliability in factual accuracy, logical thinking and computational tasks as well as Wolfram's vision for addressing these issues: plugins and LLM functions.
-
JUL 10–24 | Online
Exploring AI Foundations with Wolfram Tools
This three-part course sequence guides you in using the computational power of Wolfram technologies as a foundation for reliable AI systems. Discover concepts in machine learning, explore the Neural Net Repository and learn to use LLMs.
