Neural machine translation

Related lectures (32)

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Explores Transformers in computer vision, focusing on 'Attention Is All You Need' architecture and its applications in visual tasks.

Explores the impact of Deep learning on Digital Humanities, focusing on non conceptual knowledge systems and recent advancements in AI.

Analyzes rolling without slipping, focusing on forces, translation, rotation, and velocity components in different scenarios.

By Antoine Bosselut introduces Natural Language Processing and its challenges, advancements in neural models, and course goals.

Discusses the impact of ICT innovations in emergency response and the importance of prioritizing local communities in disaster management.

Delves into the Transformer architecture, self-attention, and training strategies for machine translation and image recognition.

Covers the impact of transformers in computer vision, discussing their architecture, applications, and advancements in various tasks.

Introduces the course on Modern Natural Language Processing, covering its significance, applications, challenges, and advancements in technology.

Covers the importance of multilingual NLP and the challenges in scaling language models.

Covers the pretraining of sequence-to-sequence models, focusing on BART and T5 architectures.