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Enseignement scientifique & technique - SD-TSIA214 : Machine Learning for Text Mining (option apprentissage statistique)

Domaine > Mathématiques.

Descriptif

Cours en anglais
This course is designed for students who will be attending classes and labs.

Objectives
Text mining is a progressing and challenging domain. For example, a lot of efforts have been recently dedicated to the development of methods able to analyze opinion data available on the social Web. The first objective of this course is to tackle the different methods of language processing and machine learning underlying text and opinion mining.


Objectifs pédagogiques

During this course, the students will acquire theoretical and technical skill on advanced machine learning methods and natural language processing. This course is designed for students who will be attending classes and labs.

Pour les étudiants du diplôme Echange international non diplomant

Machine learning (theoretical foundations) and basis of neural networks

Pour les étudiants du diplôme Diplôme d'ingénieur

Students are supposed to have followed SD-TSIA 210 Machine learning

Format des notes

Numérique sur 20

Littérale/grade européen

Pour les étudiants du diplôme Echange international non diplomant

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

La note obtenue rentre dans le calcul de votre GPA.

Pour les étudiants du diplôme Diplôme d'ingénieur

Vos modalités d'acquisition :

Evaluation : Lab report and final exam.

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

La note obtenue rentre dans le calcul de votre GPA.

Programme détaillé

The techniques and concepts that will be studied include:
-natural language pre-processing : tokenization, part-of-speech tagging, document representation and word embeddings techniques
-natural language resources : lexicons, wordnet and framenet
-text clustering and text categorization : advanced machine learning methods such as deep learning, non-negative matrix factorization, hidden markov models, etc.


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