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24
cnam/probatoire/présentation/conclusion.tex Normal file
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%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\section{Conclusion}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Conclusion}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> polyvalence
\item<2-> flexibilité
\item<3-> variété
\item<4-> disponibilité
\item<5-> évolution
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{2.5}{15}{knife}}
\only<2>{\imgh{3.5}{13}{flexible}}
\only<3>{\imgh{0}{20}{workflow}}
\only<4>{\imgh{4.25}{11.5}{tools}}
\only<5>{\imgh{6.12}{9}{evolution}}
\end{column}\end{columns}
\end{frame}

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cnam/probatoire/présentation/critics.tex Normal file
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\section{Critiques}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Avantages}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Critiques / Avantages}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> stabilité hors marge
\item<2-> régression / classification
\item<3-> alternative réseau neurones
\item<4-> précision séparation nette
\item<5-> capture relation complexe
\item<6-> grand nombre dimensions
\item<7-> dimensions > éléments
\item<8-> capacité régularisation
\item<9-> économie vecteurs support
\item<10-> non linéaire → f noyau
\item<11-> large choix f noyau
\item<12-> combinaison f noyau
\item<13-> algos grands datasets
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{0}{19}{stable}}
\only<2>{\imgh{0}{19}{classreg}}
\only<3>{\imgh{0}{8}{nn}}
\only<4>{\imgh{0}{13.5}{vast}}
\only<5>{\imgh{0}{11.5}{complex}}
\only<6>{\imgh{0}{11.5}{3d}}
\only<7>{\imgh{0}{11.5}{tiny}}
\only<8>{\imgh{0}{13.5}{fitting}}
\only<9>{\imgh{0}{13.5}{ram}}
\only<10>{\imgh{0}{19}{nonlinear}}
\only<11>{\imgh{0}{16}{functions}}
\only<12>{\imgh{0}{13.5}{hyperplanes}}
\only<13>{\imgh{0}{10}{new}}
\end{column}\end{columns}
\end{frame}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Inconvénients}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Critiques / Inconvénients}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> choix fonction noyau
\item<2-> mémoire vecteurs support
\item<3-> identification paramètres
\item<4-> temps entraînement
\item<5-> coût calculs probabilité
\item<6-> interprétation humaine
\item<7-> effet boîte noire
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{0}{14}{kernels}}
\only<2>{\imgh{1.5}{11}{pacram}}
\only<3>{\imgh{1.75}{10.5}{grid}}
\only<4>{\imgh{1.5}{11}{time}}
\only<5>{\imgh{0.5}{13}{load}}
\only<6>{\imgh{1.75}{10.5}{model}}
\only<7>{\imgh{0.85}{13.5}{box}}
\end{column}\end{columns}
\end{frame}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Limitations}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Critiques / Limitations}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> recouvrements
\item<2-> normalisations
\item<3-> multi-classes
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{2.6}{12.5}{overlap}}
\only<2>{\imgh{3.9}{10}{normalization}}
\only<3>{\imgh{0}{19}{multiclass}}
\end{column}\end{columns}
\end{frame}

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cnam/probatoire/présentation/examples.tex Normal file
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\section{Exemples}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Linéaire}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Exemples / Linéaire / Large}
\begin{center}
\only<1>{Dataset très bien distribué\\
 \\
\imgbig{ex-linear-plot}}
\only<2>{Séparation à Vaste Marge très nette\\
 \\
\imgbig{ex-linear-svm}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Exemples / Linéaire / Souple}
\begin{center}
\only<1>{Anomalies dans le dataset, violations de marge\\
 \\
\imgbig{ex-linear-out}}
\only<2>{Différentes séparations à marge souple, variation de C\\
 \\
\imgbig{ex-linear-soft}}
\end{center}
\end{frame}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Non linéaire}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Exemples / Non linéaire}
\begin{center}
\only<1>{Dataset inséparable de façon linéaire\\
 \\
\imgbig{ex-nonlinear-plot}}
\only<2>{$X_{1}=x_{1}^{2}$ ; $X_{2}=x_{2}^{2}$ ; $X_{3}=\sqrt{2} × x_{1} × x_{2}$\\
 \\
\imgbig{ex-nonlinear-linear}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Exemples / Non linéaire}
\begin{center}
\only<1>{Projection de la marge de séparation dans l’espace d’origine\\
 \\
\imgbig{ex-nonlinear-sv}}
\only<2>{Fonction de décision non linéaire dans l’espace d’origine\\
 \\
\imgbig{ex-nonlinear-svm}}
\end{center}
\end{frame}

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\section{Introduction}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Introduction}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> systèmes d’information
\item<2-> données massives
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{0}{10}{is}}
\only<2>{\imgh{0}{11}{bd}}
\end{column}\end{columns}
\end{frame}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Machine learning}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Introduction / Machine learning}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> compréhension données
\item<2-> apprentissage automatique
\item<3-> conservation généralisation
\item<4-> choix algorithme pertinent
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{4.75}{8.5}{datavis}}
\only<2>{\imgh{2}{14}{ml}}
\only<3>{\imgh{0}{18}{general}}
\only<4>{\imgh{2.9}{13.5}{algo}}
\end{column}\end{columns}
\end{frame}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Méthodes}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Introduction / Méthodes non supervisées}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> pas d’étiquetage
\item<2-> clustering
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{0}{13}{unlabeled}}
\only<2>{\imgh{0}{13}{clusters}}
\end{column}\end{columns}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Introduction / Méthodes semi-supervisées}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> étiquetage partiel
\item<2-> mélange techniques
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{0}{10}{semi-labeled}}
\only<2>{\imgh{0}{10}{semi-learning}}
\end{column}\end{columns}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Introduction / Méthodes supervisées}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> entraînement
\item<2-> évaluation
\item<3-> régression
\item<4-> classification
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{1.5}{10.5}{training}}
\only<2>{\imgh{0.5}{12.5}{target}}
\only<3>{\imgh{0}{13.5}{regression}}
\only<4>{\imgh{0.65}{13.5}{classification}}
\end{column}\end{columns}
\end{frame}

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cnam/probatoire/présentation/plan.tex Normal file
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\AtBeginSubsection{\begin{frame}{\bititle\\Plan}
\begin{multicols}{2}
{}\vspace{1em}
\tableofcontents[currentsection,currentsubsection,
sections={1-2}]\columnbreak
{}\vspace{1em}
\tableofcontents[currentsection,currentsubsection,
sections={3-4}]\end{multicols}
\end{frame}}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\begin{document}\maketitle
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\begin{frame}{\bititle\\Plan}
\begin{multicols}{2}
{}\vspace{1em}
\tableofcontents[sections={1-2}]\columnbreak
{}\vspace{1em}
\tableofcontents[sections={3-4}]\end{multicols}
\end{frame}

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cnam/probatoire/présentation/principles.tex Normal file
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\section{Principes}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Utilisations}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> filtrage email
\item<2-> classification image
\item<3-> détection stéganographie
\item<4-> granularité texture
\item<5-> reconnaissance texte
\item<6-> expression faciale
\item<7-> reconnaissance vocale
\item<8-> structure protéine
\item<9-> diagnostic médical
\item<10-> catégorisation texte
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{2}{16}{email}}
\only<2>{\imgh{3.5}{13}{muffins}}
\only<3>{\imgh{0}{20}{steganography}}
\only<4>{\imgh{0.5}{19}{textures}}
\only<5>{\imgh{6.5}{7}{ocr}}
\only<6>{\imgh{3}{14}{faceid}}
\only<7>{\imgh{4}{12}{speech}}
\only<8>{\imgh{3}{14}{protein}}
\only<9>{\imgh{2.5}{15}{diagnosis}}
\only<10>{\imgh{5.62}{10}{texts}}
\end{column}\end{columns}
\end{frame}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Régression}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Régression / Linéaire}
\begin{center}
\only<1>{Régression linéaire, variation d’$\varepsilon$\\
 \\
\imgbig{regression_linear_left}}
\only<2>{Régression linéaire, variation d’$\varepsilon$\\
 \\
\imgbig{regression_linear_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Régression / Non linéaire}
\begin{center}
\only<1>{Régression polynomiale de degré 2, variation de $C$\\
 \\
\imgbig{regression_nonlinear_left}}
\only<2>{Régression polynomiale de degré 2, variation de $C$\\
 \\
\imgbig{regression_nonlinear_right}}
\end{center}
\end{frame}
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
\subsection{Classification}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Linéaire / Vaste}
\begin{center}
\only<1>{Séparation à Vaste Marge\\
 \\
\imgwide{margin_large_left}}
\only<2>{Séparation à Vaste Marge\\
 \\
\imgwide{margin_large_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Linéaire / Vaste}
\begin{center}
\only<1>{Changements d’échelles des dimensions\\
 \\
 \imgwide{margin_scale_left}}
\only<2>{Changements d’échelles des dimensions\\
 \\
 \imgwide{margin_scale_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Linéaire / Souple}
\begin{center}
\only<1>{Sensibilité de vaste marge aux anomalies\\
 \\
\imgwide{margin_hard_left}}
\only<2>{Sensibilité de vaste marge aux anomalies\\
 \\
\imgwide{margin_hard_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Linéaire / Souple}
\begin{center}
\only<1>{Plus ou moins de violations de marge, variation de $C$\\
 \\
\imgwide{margin_few_left}}
\only<2>{Plus ou moins de violations de marge, variation de $C$\\
 \\
\imgwide{margin_few_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Non linéaire}
\begin{center}
\only<1>{Séparation linéaire par ajout de variable\\
 \\
\imgwide{nonlinear_linear_left}}
\only<2>{Séparation linéaire par ajout de variable\\
 \\
\imgwide{nonlinear_linear_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Non linéaire}
\begin{center}
\only<1>{Classification utilisant des variables polynomiales\\
 \\
\imgbig{features_polynomial}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Non linéaire}
\begin{center}
\only<1>{Fonction noyau polynomiale\\
 \\
\imgbig{kernel_polynomial_left}}
\only<2>{Fonction noyau polynomiale\\
 \\
\imgbig{kernel_polynomial_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Non linéaire}
\begin{center}
\only<1>{Variables de similarité utilisant la RBF gaussienne\\
 \\
\imgbig{features_similar_left}}
\only<2>{Variables de similarité utilisant la RBF gaussienne\\
 \\
\imgbig{features_similar_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Non linéaire}
\begin{center}
\only<1>{Fonction noyau gaussienne (RBF)\\
 \\
\imgbig{kernel_rbf_left}
\imgbig{kernel_rbf_right}}
\end{center}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Multi-classes}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> SVM à arbre de décision
\item<2-> SVM par paires
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{0}{20}{tree}}
\only<2>{\imgh{5.25}{9.5}{pairwise}}
\end{column}\end{columns}
\end{frame}
%⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅
\begin{frame}{\bititle\\Principes / Classification / Normalisations}
\begin{columns}\begin{column}{.5\textwidth}
\begin{itemize}
\item<1-> filtre gaussien
\item<2-> réduction de bruit
\item<3-> suppression artefacts
\item<4-> égalisation histogramme
\item<5-> filtre médian
\end{itemize}
\end{column}\begin{column}{.5\textwidth}
\only<1>{\imgh{0}{19}{gaussian}}
\only<2>{\imgh{0.12}{20}{noise}}
\only<3>{\imgh{0.12}{20}{artifacts}}
\only<4>{\imgh{0.75}{17.5}{histogram}}
\only<5>{\imgh{0.12}{20}{median}}
\end{column}\end{columns}
\end{frame}

31
cnam/probatoire/présentation/settings.tex Normal file
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\documentclass[aspectratio=43]{beamer}
\usetheme{Berkeley}
\usecolortheme{seahorse}
\usebackgroundtemplate{\includegraphics[width=\paperwidth]{../paper}}
\setbeamercovered{transparent}
\beamertemplatenavigationsymbolsempty
\addtobeamertemplate{navigation symbols}{}{
\color{black}\normalsize\textbf\insertframenumber}
\newcommand{\img}[2]{\includegraphics[#1]{images/#2}}
\newcommand{\imgbig}[1]{\img{height=16em}{#1}}
\newcommand{\imgcol}[1]{\img{width=.86\textwidth}{#1}}
\newcommand{\imgh}[3]{\vspace{#1em}\img{height=#2em}{#3}\vspace{#1em}}
\newcommand{\imgwide}[1]{\img{height=12em}{#1}}
\newcommand{\imgwidth}[1]{\img{width=\textwidth}{#1}}
\def\hi{SVM}
\def\lo{Machine à Vecteurs de Support}
\def\bititle{\hi, \lo}
\logo{\includegraphics[height=7.5em]{../cnam}}
\title[\hi]{\hi}
\subtitle{\lo}
\author[M. Beninca]{Marc Beninca}
\institute[CNAM]{Conservatoire National des Arts et Métiers}
\date[Probatoire 2020]{Oral probatoire\\Mercredi 16 Septembre 2020}
\hypersetup{colorlinks,linkcolor=blue,urlcolor=blue}
\usepackage{fontspec}
\setmainfont{DejaVu Sans}\setmonofont{DejaVu Sans Mono}
\usepackage{multicol}