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Faculté des Sciences appliquées
Faculté des Sciences appliquées
MASTER THESIS
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Master thesis : Optimization Techniques for AutoML systems

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Vieslet, Thomas ULiège
Promotor(s) : Geurts, Pierre ULiège
Date of defense : 28-Jan-2022 • Permalink : http://hdl.handle.net/2268.2/13920
Details
Title : Master thesis : Optimization Techniques for AutoML systems
Translated title : [fr] Techniques d'optimisation pour des systèmes AutoML
Author : Vieslet, Thomas ULiège
Date of defense  : 28-Jan-2022
Advisor(s) : Geurts, Pierre ULiège
Committee's member(s) : Louppe, Gilles 
Louveaux, Quentin 
Lahouli, Ichraf 
Language : English
Number of pages : 72
Keywords : [en] AutoML, Optimization Techniques
Discipline(s) : Engineering, computing & technology > Computer science
Target public : Researchers
Professionals of domain
Student
General public
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master : ingénieur civil en science des données, à finalité spécialisée
Faculty: Master thesis of the Faculté des Sciences appliquées

Abstract

[en] In this Master Thesis is investigated several optimization techniques in the context of automatizing the Machine Learning Pipeline. The goal is to use these techniques to find the best set of features together with best model with the best hyperparameters values. The performance of the techniques are compared on various tasks.


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Description: The link to the code is on page 3
Size: 6.03 MB
Format: Adobe PDF
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Author

  • Vieslet, Thomas ULiège Université de Liège > Master ingé. civ. sc. don. à . fin.

Promotor(s)

Committee's member(s)

  • Louppe, Gilles
  • Louveaux, Quentin
  • Lahouli, Ichraf
  • Total number of views 26
  • Total number of downloads 4










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