Sigal Shaked
Sigal Shaked is a founder, technologist, and researcher with over 20 years of experience at the intersection of data, machine learning, and Generative AI. She holds a PhD in Software and Information Systems Engineering and was among the early academic contributors to the emerging field of GenAI. At Datomize, she led the development of a GenAI-powered synthetic data platform, and today, at Datawizz, she focuses on building domain-specific small language models (SLMs) that prioritize performance, privacy, and real-world utility.
Session
A hands-on guide to fine-tuning small language models (SLMs) using Python tools like transformers, unsloth, and trl. Learn practical workflows that empower data teams to build performant, private, and domain-specific LLMs.