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added risks chapter

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Clemens Dautermann 2020-01-23 16:38:18 +01:00
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doc/Grundlagen_des_maschinellen_lernens.toc
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\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {1.3}Gefahren von maschinellem Lernen}{5}{subsection.1.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {1.3.1}Eignung der Datens\IeC {\"a}tze}{5}{subsubsection.1.3.1}%
\contentsline {subsubsection}{\numberline {1.3.1}Overfitting}{5}{subsubsection.1.3.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {1.3.2}Overfitting}{5}{subsubsection.1.3.2}%
\contentsline {subsubsection}{\numberline {1.3.2}Die Daten}{5}{subsubsection.1.3.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {1.3.3}Unbewusste Manipulation der Daten}{5}{subsubsection.1.3.3}%
\contentsline {section}{\numberline {2}Verschiedene Techniken maschinellen Lernens}{6}{section.2}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {2}Verschiedene Techniken maschinellen lernens}{5}{section.2}%
\contentsline {subsection}{\numberline {2.1}\IeC {\"U}berwachtes Lernen}{6}{subsection.2.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {2.1}\IeC {\"U}berwachtes Lernen}{5}{subsection.2.1}%
\contentsline {subsection}{\numberline {2.2}Un\IeC {\"u}berwachtes Lernen}{6}{subsection.2.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {2.2}Un\IeC {\"u}berwachtes Lernen}{5}{subsection.2.2}%
\contentsline {subsection}{\numberline {2.3}Best\IeC {\"a}rkendes Lernen}{6}{subsection.2.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {2.3}Best\IeC {\"a}rkendes Lernen}{5}{subsection.2.3}%
\contentsline {section}{\numberline {3}Neuronale Netze}{6}{section.3}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {3}Neuronale Netze}{5}{section.3}%
\contentsline {subsection}{\numberline {3.1}Maschinelles Lernen und menschliches Lernen}{7}{subsection.3.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {3.1}Maschinelles Lernen und menschliches Lernen}{5}{subsection.3.1}%
\contentsline {subsection}{\numberline {3.2}Der Aufbau eines neuronalen Netzes}{8}{subsection.3.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {3.2}Der Aufbau eines neuronalen Netzes}{6}{subsection.3.2}%
\contentsline {subsection}{\numberline {3.3}Berechnung des Ausgabevektors}{9}{subsection.3.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {3.3}Berechnung des Ausgabevektors}{7}{subsection.3.3}%
\contentsline {subsection}{\numberline {3.4}Der Lernprozess}{11}{subsection.3.4}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {3.4}Der Lernprozess}{9}{subsection.3.4}%
\contentsline {subsection}{\numberline {3.5}Fehlerfunktionen}{11}{subsection.3.5}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {3.5}Fehlerfunktionen}{10}{subsection.3.5}%
\contentsline {subsubsection}{\numberline {3.5.1}MSE -- Durchschnittlicher quadratischer Fehler}{11}{subsubsection.3.5.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.5.1}MSE -- Durchschnittlicher quadratischer Fehler}{10}{subsubsection.3.5.1}%
\contentsline {subsubsection}{\numberline {3.5.2}MAE -- Durchschnitztlicher absoluter Fehler}{12}{subsubsection.3.5.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.5.2}MAE -- Durchschnitztlicher absoluter Fehler}{10}{subsubsection.3.5.2}%
\contentsline {subsubsection}{\numberline {3.5.3}Kreuzentropiefehler}{12}{subsubsection.3.5.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.5.3}Kreuzentropiefehler}{11}{subsubsection.3.5.3}%
\contentsline {subsection}{\numberline {3.6}Gradientenverfahren und Backpropagation}{13}{subsection.3.6}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {3.6}Gradientenverfahren und Backpropagation}{12}{subsection.3.6}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.6.1}Lernrate}{13}{subsubsection.3.6.1}%
\contentsline {subsubsection}{\numberline {3.6.1}Lernrate}{14}{subsubsection.3.6.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {3.7}Verschiedene Layerarten}{14}{subsection.3.7}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.7.1}Convolutional Layers}{14}{subsubsection.3.7.1}%
\contentsline {subsubsection}{\numberline {3.7.1}Convolutional Layers}{15}{subsubsection.3.7.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsubsection}{\numberline {3.7.2}Pooling Layers}{16}{subsubsection.3.7.2}%
\contentsline {subsubsection}{\numberline {3.7.2}Pooling Layers}{18}{subsubsection.3.7.2}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {4}PyTorch}{19}{section.4}%
\contentsline {section}{\numberline {4}PyTorch}{21}{section.4}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {4.1}Datenvorbereitung}{19}{subsection.4.1}%
\contentsline {subsection}{\numberline {4.1}Datenvorbereitung}{21}{subsection.4.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {4.2}Definieren des Netzes}{19}{subsection.4.2}%
\contentsline {subsection}{\numberline {4.2}Definieren des Netzes}{21}{subsection.4.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {4.3}Trainieren des Netzes}{19}{subsection.4.3}%
\contentsline {subsection}{\numberline {4.3}Trainieren des Netzes}{21}{subsection.4.3}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {5}Fallbeispiel I:\newline Ein Klassifizierungsnetzwerk f\IeC {\"u}r handgeschriebene Ziffern}{19}{section.5}%
\contentsline {section}{\numberline {5}Fallbeispiel I:\newline Ein Klassifizierungsnetzwerk f\IeC {\"u}r handgeschriebene Ziffern}{21}{section.5}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.1}Aufgabe}{19}{subsection.5.1}%
\contentsline {subsection}{\numberline {5.1}Aufgabe}{21}{subsection.5.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.2}Der MNIST Datensatz}{19}{subsection.5.2}%
\contentsline {subsection}{\numberline {5.2}Der MNIST Datensatz}{21}{subsection.5.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.3}Fragmentbasierte Erkennung}{19}{subsection.5.3}%
\contentsline {subsection}{\numberline {5.3}Fragmentbasierte Erkennung}{21}{subsection.5.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {5.4}Ergebnis}{19}{subsection.5.4}%
\contentsline {subsection}{\numberline {5.4}Ergebnis}{21}{subsection.5.4}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {6}Fallbeispiel II:\newline Eine selbsttrainierende KI f\IeC {\"u}r Tic-Tac-Toe}{19}{section.6}%
\contentsline {section}{\numberline {6}Fallbeispiel II:\newline Eine selbsttrainierende KI f\IeC {\"u}r Tic-Tac-Toe}{21}{section.6}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.1}Das Prinzip}{19}{subsection.6.1}%
\contentsline {subsection}{\numberline {6.1}Das Prinzip}{21}{subsection.6.1}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.2}Chance-Tree Optimierung}{19}{subsection.6.2}%
\contentsline {subsection}{\numberline {6.2}Chance-Tree Optimierung}{21}{subsection.6.2}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.3}L\IeC {\"o}sung mittels eines neuronalen Netzes}{19}{subsection.6.3}%
\contentsline {subsection}{\numberline {6.3}L\IeC {\"o}sung mittels eines neuronalen Netzes}{21}{subsection.6.3}%
\defcounter {refsection}{0}\relax
\contentsline {subsection}{\numberline {6.4}Vergleich}{19}{subsection.6.4}%
\contentsline {subsection}{\numberline {6.4}Vergleich}{21}{subsection.6.4}%
\defcounter {refsection}{0}\relax
\contentsline {section}{\numberline {7}Schlusswort}{19}{section.7}%
\contentsline {section}{\numberline {7}Schlusswort}{21}{section.7}%