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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NOV 26 | Online
Big Problems with Big Data: Managing Risks in AI
This talk explores the issues you need to consider in making data-driven decisions. It discusses topics such as when machine learning is appropriate, sources of bias, validation and explainability of models and decision-making criteria.
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Dec 9 | Online
Statistics and Machine Learning: Better Together
This example-driven exploration showcases how the symbolic nature of Wolfram Language makes the handling of statistical distributions simple, how automation makes machine learning accessible and how the two fields together can utilize powerful and flexible tools.
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JAN 5–16 | Online
Wolfram Neural Networks Boot Camp
Learn about neural networks, how you can use pre-trained networks and how to build and train your own models in this two-week online boot camp. Interact with Wolfram experts; explore ways that AI and deep learning can be applied to text, image and audio analysis; and earn Wolfram certifications.
