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Explore machine translation fundamentals through this 3-hour lecture from the JSALT 2025 summer school, focusing on natural language processing with transformer-based models. Delve into the core concepts and methodologies of machine translation systems, examining how transformer architectures revolutionize the field of automated language translation. Learn about the theoretical foundations and practical applications of transformer models in NLP, with specific emphasis on their implementation in machine translation tasks. Gain insights into state-of-the-art approaches for building and optimizing translation systems using modern deep learning techniques. Access comprehensive slide materials that cover essential topics in transformer-based machine translation, providing both theoretical understanding and practical knowledge for researchers and practitioners in computational linguistics and natural language processing.
