\babel@toc {english}{}
\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}%