Vortrag-Martin.tex 2.5 KB

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  1. \documentclass[hyperref={pdfpagelabels=false},usepdftitle=false]{beamer}
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  50. \begin{document}
  51. \title{Art in Machine Learning}
  52. \subtitle{\href{https://github.com/MartinThoma/}{github.com/MartinThoma/}}
  53. \author{Martin Thoma}
  54. \date{15. Januar 2016}
  55. \subject{Machine Learning}
  56. \frame{\titlepage}
  57. \section{Examples}
  58. \subsection{Examples}
  59. %\framedgraphiconly{0099.jpg}
  60. \incgraph{0099.jpg}
  61. \section{ML-Basics}
  62. \subsection{ML-Basics}
  63. \begin{frame}{Was ist Machine Learning?}
  64. \begin{block}{Definition by Tom Mitchell: ML}
  65. A computer program is said to learn from \textbf{experience} $E$ with
  66. respect to some class of \textbf{tasks} $T$ and \textbf{performance
  67. measure} $P$, if its performance at tasks in $T$, as measured by $P$,
  68. improves with experience $E$.
  69. \end{block}
  70. \end{frame}
  71. \end{document}