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--- en:list [2007/12/17 10:53] – quostben
+++ en:list [2010/03/09 16:53] – quostben
@@ Line 38: / Line 38: @@
 ===== Linear and non-linear optimization =====
-([[http://www.dma.utc.fr/polytex/cours.pdf|link]] towards the unit course)
+([[http://www.hds.utc.fr/ro04|link]] towards the unit web page)
 The unit introduces the basic techniques in linear programming (simplex method, duality), integer programming, and non-linear optimization (gradient methods, Newton and quasi-Newton methods).
@@ Line 51: / Line 51: @@
-===== Data analysis and data mining =====
+===== Data analysis, Data Mining ; decision, diagnosis, machine learning =====
-([[http://www.hds.utc.fr/sy09|link]] towards the unit web page)
+(Links towards the web pages of [[http://www.hds.utc.fr/sy09|SY09]] and [[http://www.hds.utc.fr/sy19|SY19]])
-This unit aims at presenting modern techniques of large data sets, and basic tools for data mining.
+Both units aim at presenting the modern techniques for analysing large data sets and the basic notions and tools of data mining to the students. Both supervised and unsupervised learning are studied.
-Notions of principal component analysis, discriminant analysis, multidimensional scaling, as well as unsupervised classification, are presented. Mixture models for classification are as well studied in this course.
+Notions of principal component analysis, factor discriminant analysis, multidimensional scaling, as well as unsupervised clustering (in particular using mixture models) are described. The theory of decision, the notions of optimal classification are also presented, as well as the algorithms for learning decision trees, neural networks, or support vector machines.
+These unit courses are destinated to students at the end of their degree course.
-This unit course is destinated to students at the end of their degree course.

UMR CNRS 7253

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