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Machine learning for NLP 3

  • ECTS

    9 crédits



In this course we introduce deep learning methods for natural language processing. The notions of lexical embedding, recurrent networks, sequence-to-sequence transduction models and transformers are presented. Finally, the course presents the interface between deep learning and structured learning methods: labeling of sentences into parts of speech and syntactic analysis. We also introduce transfer learning and the training and usage of pre-trained language models in neural NLP models.

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