Machine Translation: Sequence-to-Sequence and Attention
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Provides an overview of Natural Language Processing, focusing on transformers, tokenization, and self-attention mechanisms for effective language analysis and synthesis.
Explores pretraining sequence-to-sequence models with BART and T5, discussing transfer learning, fine-tuning, model architectures, tasks, performance comparison, summarization results, and references.
