Advanced Techniques and Interpretability in LLMs

О курсе

Delve into advanced transformer techniques, including generative AI, fine-tuning, interpretability, and the critical role of tokenization. Learn how to leverage and interpret large language models for a variety of sophisticated NLP tasks. This course covers the next level of transformer applications, focusing on generative AI with models like ChatGPT, advanced fine-tuning strategies, and the interpretability of model outputs. Learners will explore how tokenization shapes model performance, how embeddings can be used for search and transfer learning, and how to apply transformers to tasks such as semantic role labeling and summarization. By completing this course, you will be able to implement, fine-tune, and interpret large language models for complex NLP challenges. The course combines in-depth conceptual discussions with practical demonstrations, guiding learners through the intricacies of advanced transformer techniques and interpretability tools. Each topic is presented with clarity to ensure learners can apply these methods confidently. This course is part two of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Transformers for Natural Language Processing and Computer Vision, by Denis Rothman. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Навыки, которые вы освоите

Учитесь у экспертов

Packt - Course Instructors

Преподаватель курса