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Enseignement scientifique & technique - APM_5AI27_TP : Large-scale Generative Models for NLP and Speech Processing

Domaine > Image-Données-Signal.

Descriptif

Natural language processing has given rise to innumerable industrial applications. While many new tasks have emerged in NLP and speech processing over the last decades, methods to solve them have increasingly converged towards a unified modeling paradigm. In this course, we will use large-scale generative models and sequence-to-sequence modeling to delve into state-of-the-art statistical machine learning methods and apply them to major NLP and speech processing tasks — language modeling, machine translation, speech recognition, information extraction. Students should expect to get an in-depth understanding of these methods, through theoretical analysis and hands-on lab sessions. Grading will involve a project, to be carried out over the course of the class. Topics to be covered:
1. Language Modeling
2. Speech to Text
3. Extracting Structured Information from Text
4. Machine Translation
5. Code Generation

Format des notes

Numérique sur 20

Littérale/grade américain

Pour les étudiants du diplôme Master M1 - Data and Artificial Intelligence

Pour les étudiants du diplôme Diplôme d'ingénieur

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 2 ECTS
  • Crédit d'Option 3A acquis : 2

Pour les étudiants du diplôme Programme de mobilité des établissements français partenaires

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 2 ECTS
  • Crédit d'Option 3A acquis : 2

Pour les étudiants du diplôme Master M2 - Data & Artificial Intelligence

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 2.5 ECTS

Pour les étudiants du diplôme Echange international non diplomant

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 2 ECTS

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