Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Explore advanced natural language processing concepts through this comprehensive lecture series from Carnegie Mellon University taught by Graham Neubig. Master fundamental NLP techniques starting with text classification and language modeling, then progress to sophisticated neural network architectures including recurrent networks, attention mechanisms, and transformer models. Delve into cutting-edge topics such as pre-training methods, multi-task learning across domains and languages, and prompting strategies for large language models. Learn practical skills for experimental design, model interpretation, and debugging NLP systems. Examine specialized applications including question answering systems, dialog systems, information extraction, and knowledge-based reasoning. Study linguistic foundations covering word segmentation, morphology, syntax, semantics, and discourse analysis. Investigate advanced modeling techniques for handling long sequences, structured learning algorithms, latent variable models, and adversarial methods. Address critical issues of bias and fairness in NLP systems while gaining hands-on experience with state-of-the-art pre-trained models and their practical implementation.
