Master TAL - MSc. NLP

Course Unit

Neural network

UE

901

EC

EC1

Hours

27h

Course Description

This course provides a comprehensive view of machine learning and neural networks,
starting from multilayer perceptrons to advanced architectures currently used
(deterministic/probabilistic networks, convolutive networks (CNN), and recurrent networks (RNN).
We survey the fundamentals of neural network algorithms, and we introduce several properties that aid in the selection of the most appropriate architectures of networks depending on the task at hand.

 

Learning Outcome

  • Expertise in neural network theories
  • Application of these theories from problem-solving

Prerequisites

  • UE 801

Targeted Skills

  • Analyse a problem before computationally treating spoken or written data
  • Know how to apply algorithmic techniques, linguistic analysis, statistics, and knowledge processing.

Professor

Emmanuel Vincent

Inria

More Information

Bibliography

Evaluation procedures

Number of Tests

  • 2

Number of the tests

  • Written exam (1) and multiple choice exam (1)

Group work

  • Software project (group of 2 people)

Combine with other specialization

  • MSc Cognitive Science

Back to MSc Sciences Cognitives

Back to Master TAL - MSc. NLP