Finetuning Open-Source LLMs // LLMs in Production Conference 3 Keynote 1
Speakers

Sebastian Raschka been working on machine learning and AI for more than a decade.
Next to being a researcher, Sebastian also has a strong passion for education and am best known for my bestselling books on machine learning using open-source software.
After his PhD, Sebastian joined the University of Wisconsin-Madison as an assistant professor in the Department of Statistics, where he focused deep learning and machine learning research until 2023.
Taking a yearlong break from academia, Sebastian joined Lightning AI in 2022, where he now focuses on AI and LLM research, developing open-source software, and creating educational material.

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.
SUMMARY
This tutorial starts by surveying the different ways we can use LLMs. Then, we will take a deeper dive into various LLM finetuning strategies, such as low-rank adaptation, and learn how we can create custom LLMs using open-source software.

