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started convolution section

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Clemens Dautermann 2020-01-13 14:07:17 +01:00
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doc/Grundlagen_des_maschinellen_lernens.toc
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\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.7.1}Convolutional Layers}{13}{subsubsection.3.7.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.7.2}Pooling Layers}{13}{subsubsection.3.7.2}%
\contentsline {subsubsection}{\numberline {3.7.2}Pooling Layers}{15}{subsubsection.3.7.2}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {4}PyTorch}{13}{section.4}%
\contentsline {section}{\numberline {4}PyTorch}{15}{section.4}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {4.1}Datenvorbereitung}{13}{subsection.4.1}%
\contentsline {subsection}{\numberline {4.1}Datenvorbereitung}{15}{subsection.4.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {4.2}Definieren des Netzes}{13}{subsection.4.2}%
\contentsline {subsection}{\numberline {4.2}Definieren des Netzes}{15}{subsection.4.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {4.3}Trainieren des Netzes}{13}{subsection.4.3}%
\contentsline {subsection}{\numberline {4.3}Trainieren des Netzes}{15}{subsection.4.3}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {5}Fallbeispiel I:\newline Ein Klassifizierungsnetzwerk f\IeC {\"u}r handgeschriebene Ziffern}{13}{section.5}%
\contentsline {section}{\numberline {5}Fallbeispiel I:\newline Ein Klassifizierungsnetzwerk f\IeC {\"u}r handgeschriebene Ziffern}{15}{section.5}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.1}Aufgabe}{13}{subsection.5.1}%
\contentsline {subsection}{\numberline {5.1}Aufgabe}{15}{subsection.5.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.2}Der MNIST Datensatz}{13}{subsection.5.2}%
\contentsline {subsection}{\numberline {5.2}Der MNIST Datensatz}{15}{subsection.5.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.3}Fragmentbasierte Erkennung}{13}{subsection.5.3}%
\contentsline {subsection}{\numberline {5.3}Fragmentbasierte Erkennung}{15}{subsection.5.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.4}Ergebnis}{13}{subsection.5.4}%
\contentsline {subsection}{\numberline {5.4}Ergebnis}{15}{subsection.5.4}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {6}Fallbeispiel II:\newline Eine selbsttrainierende KI f\IeC {\"u}r Tic-Tac-Toe}{13}{section.6}%
\contentsline {section}{\numberline {6}Fallbeispiel II:\newline Eine selbsttrainierende KI f\IeC {\"u}r Tic-Tac-Toe}{15}{section.6}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.1}Das Prinzip}{13}{subsection.6.1}%
\contentsline {subsection}{\numberline {6.1}Das Prinzip}{15}{subsection.6.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.2}Chance-Tree Optimierung}{13}{subsection.6.2}%
\contentsline {subsection}{\numberline {6.2}Chance-Tree Optimierung}{15}{subsection.6.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.3}L\IeC {\"o}sung mittels eines neuronalen Netzes}{13}{subsection.6.3}%
\contentsline {subsection}{\numberline {6.3}L\IeC {\"o}sung mittels eines neuronalen Netzes}{15}{subsection.6.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.4}Vergleich}{13}{subsection.6.4}%
\contentsline {subsection}{\numberline {6.4}Vergleich}{15}{subsection.6.4}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {7}Schlusswort}{13}{section.7}%
\contentsline {section}{\numberline {7}Schlusswort}{15}{section.7}%