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Output written on main.dvi (36 pages, 66348 bytes).
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Output written on main.dvi (36 pages, 72912 bytes).
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\vspace{0.8cm}
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\includegraphics[width=.7\linewidth]{frontpage.jpg}
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\includegraphics[width=.7\linewidth]{frontpage}
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\Large
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Università degli Studi di Milano
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@ -1,30 +1,30 @@
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\babel@toc {english}{}
|
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\contentsline {section}{\numberline {1}Lecture 1 - 09-03-2020}{2}%
|
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\contentsline {subsection}{\numberline {1.1}Introduction}{2}%
|
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\contentsline {section}{\numberline {2}Lecture 2 - 07-04-2020}{5}%
|
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\contentsline {subsection}{\numberline {2.1}Argomento}{5}%
|
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\contentsline {subsection}{\numberline {2.2}Loss}{5}%
|
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\contentsline {subsubsection}{\numberline {2.2.1}Absolute Loss}{5}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.2}Square Loss}{6}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.3}Example of information of square loss}{6}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.4}labels and losses}{8}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.5}Example TF(idf) documents encoding}{9}%
|
||||
\contentsline {section}{\numberline {3}Lecture 3 - 07-04-2020}{11}%
|
||||
\contentsline {subsection}{\numberline {3.1}Overfitting}{13}%
|
||||
\contentsline {subsubsection}{\numberline {3.1.1}Noise in the data}{13}%
|
||||
\contentsline {subsection}{\numberline {3.2}Underfitting}{15}%
|
||||
\contentsline {subsection}{\numberline {3.3}Nearest neighbour}{15}%
|
||||
\contentsline {section}{\numberline {4}Lecture 4 - 07-04-2020}{17}%
|
||||
\contentsline {subsection}{\numberline {4.1}Computing $h_{NN}$}{17}%
|
||||
\contentsline {subsection}{\numberline {4.2}Tree Predictor}{18}%
|
||||
\contentsline {section}{\numberline {5}Lecture 5 - 07-04-2020}{21}%
|
||||
\contentsline {subsection}{\numberline {5.1}Tree Classifier}{21}%
|
||||
\contentsline {subsection}{\numberline {5.2}Jensen’s inequality}{22}%
|
||||
\contentsline {subsection}{\numberline {5.3}Tree Predictor}{24}%
|
||||
\contentsline {subsection}{\numberline {5.4}Statistical model for Machine Learning}{25}%
|
||||
\contentsline {section}{\numberline {6}Lecture 6 - 07-04-2020}{27}%
|
||||
\contentsline {section}{\numberline {7}Lecture 7 - 07-04-2020}{28}%
|
||||
\contentsline {section}{\numberline {8}Lecture 8 - 07-04-2020}{29}%
|
||||
\contentsline {section}{\numberline {9}Lecture 9 - 07-04-2020}{30}%
|
||||
\contentsline {section}{\numberline {10}Lecture 10 - 07-04-2020}{31}%
|
||||
\contentsline {subsection}{\numberline {10.1}TO BE DEFINE}{31}%
|
||||
\contentsline {section}{\numberline {1}Lecture 1 - 09-03-2020}{3}%
|
||||
\contentsline {subsection}{\numberline {1.1}Introduction}{3}%
|
||||
\contentsline {section}{\numberline {2}Lecture 2 - 07-04-2020}{6}%
|
||||
\contentsline {subsection}{\numberline {2.1}Argomento}{6}%
|
||||
\contentsline {subsection}{\numberline {2.2}Loss}{6}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.1}Absolute Loss}{6}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.2}Square Loss}{7}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.3}Example of information of square loss}{7}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.4}labels and losses}{9}%
|
||||
\contentsline {subsubsection}{\numberline {2.2.5}Example TF(idf) documents encoding}{10}%
|
||||
\contentsline {section}{\numberline {3}Lecture 3 - 07-04-2020}{12}%
|
||||
\contentsline {subsection}{\numberline {3.1}Overfitting}{14}%
|
||||
\contentsline {subsubsection}{\numberline {3.1.1}Noise in the data}{14}%
|
||||
\contentsline {subsection}{\numberline {3.2}Underfitting}{16}%
|
||||
\contentsline {subsection}{\numberline {3.3}Nearest neighbour}{16}%
|
||||
\contentsline {section}{\numberline {4}Lecture 4 - 07-04-2020}{18}%
|
||||
\contentsline {subsection}{\numberline {4.1}Computing $h_{NN}$}{18}%
|
||||
\contentsline {subsection}{\numberline {4.2}Tree Predictor}{19}%
|
||||
\contentsline {section}{\numberline {5}Lecture 5 - 07-04-2020}{22}%
|
||||
\contentsline {subsection}{\numberline {5.1}Tree Classifier}{22}%
|
||||
\contentsline {subsection}{\numberline {5.2}Jensen’s inequality}{23}%
|
||||
\contentsline {subsection}{\numberline {5.3}Tree Predictor}{25}%
|
||||
\contentsline {subsection}{\numberline {5.4}Statistical model for Machine Learning}{26}%
|
||||
\contentsline {section}{\numberline {6}Lecture 6 - 07-04-2020}{28}%
|
||||
\contentsline {section}{\numberline {7}Lecture 7 - 07-04-2020}{29}%
|
||||
\contentsline {section}{\numberline {8}Lecture 8 - 07-04-2020}{30}%
|
||||
\contentsline {section}{\numberline {9}Lecture 9 - 07-04-2020}{31}%
|
||||
\contentsline {section}{\numberline {10}Lecture 10 - 07-04-2020}{32}%
|
||||
\contentsline {subsection}{\numberline {10.1}TO BE DEFINE}{32}%
|
||||
|
||||
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