Introduction to Transformer Models for NLP: Unit 1
By Coursera
on Coursera
· Data Science
About This Course
This course covers the development of natural language processing (NLP), starting with basic concepts and moving to modern transformer architectures. You will learn about attention mechanisms and their impact on language modeling, as well as the details of transformer models, including scaled dot product attention and multi-headed attention. The course includes practical exercises in transfer learning using pre-trained models such as BERT and GPT, with instruction on fine-tuning these models for specific NLP tasks in PyTorch. By the end, you will understand the theory behind current NLP models and gain practical experience in applying them to real-world problems.
Instructor
Pearson
Frequently Asked Questions
How much does Introduction to Transformer Models for NLP: Unit 1 cost?
Visit the Introduction to Transformer Models for NLP: Unit 1 course page for current pricing and available discounts.
Who teaches Introduction to Transformer Models for NLP: Unit 1?
Introduction to Transformer Models for NLP: Unit 1 is taught by Pearson, Pearson.
What skill level is Introduction to Transformer Models for NLP: Unit 1 for?
This course is designed for beginner learners.