ics5110_ml_handbook.tex

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% Front matter
\frontmatter

% r.3 full title page
%% \maketitle


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\par Copyright \copyright\ \the\year\ \ics\ class of 2018/9, University of Malta.










\par\smallcaps{Jean-Paul Ebejer, Dylan Seychell, Lara Marie Demajo, Daniel Farrugia, Keith Mintoff, Franco Cassar Manghi, David Farrugia, Ivan Salomone, Andrew Cachia, Jake J.\ Dalli, Joseph Azzopardi, Natalia Mallia, Mark Muscat, Stefan Cassar, Patrick Bezzina, Dylan Vassallo, Brian Pace, George Eduardo Buckup Sulzbeck, Katrin Jansen, Aliia Erofeeva, Michael Filletti, Neil Farrugia, Claire Galea, Albert Bezzina, Philip Mifsud, Neil Micallef, Matthew Farrugia, Samuel Mizzi, Aaron Grech, Peter Incorvaja} %TODO


\par Licensed under the Apache License, Version 2.0 (the ``License''); you may not
use this file except in compliance with the License. You may obtain a copy
of the License at \url{http://www.apache.org/licenses/LICENSE-2.0}. Unless
required by applicable law or agreed to in writing, software distributed
under the License is distributed on an \smallcaps{``AS IS'' BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND}, either express or implied. See the
License for the specific language governing permissions and limitations
under the License.\index{license}

\par\textit{First printing, \monthyear}
\end{fullwidth}

% r.5 contents
\tableofcontents

%%\listoffigures

%%\listoftables

% r.9 introduction
\cleardoublepage
\chapter{Introduction}

This book explains popular Machine Learning terms.  We focus to explain each term comprehensively, through the use of examples and diagrams.  The description of each term is written by a student sitting in for \ics\footnote{\url{https://www.um.edu.mt/courses/studyunit/ICS5110}} at the University of Malta (class 2018/2019).  This study-unit is part of the MSc.\ in AI offered by the Department of Artificial Intelligence, Faculty of ICT.

%%
% Start the main matter (normal chapters)
\mainmatter

%% JP's example file -- file must be stored in directory "terms" and have
%% the term and initials of the student in the filename.
\input{terms/activationfunctions_km.tex}
\input{terms/bayesianmodels_kj.tex}
\input{terms/classification_cg.tex}
\input{terms/conceptdrift_mf.tex}
\input{terms/confusionmatrix_df.tex}
\input{terms/convolution_gebs.tex}
\input{terms/crossvalidation_lmd.tex}
\input{terms/dimensionalityreduction_sc.tex}
\input{terms/empiricalriskminimisation_nf.tex}
\input{terms/ensemblemethods_dv.tex}
\input{terms/evaluationmethods_ae.tex}
\input{terms/featureselection_ab.tex}
\input{terms/generativemodels_pm.tex}
\input{terms/hyperparameters_nm.tex}
\input{terms/longshorttermmemory_nm.tex}
\input{terms/lossfunctions_ag.tex}
\input{terms/neuralnetwork_bp.tex}
\input{terms/noiseindatasets_is.tex}
\input{terms/onlinelearning_df.tex}
\input{terms/regularisationofmodels_ja.tex}
\input{terms/roccurves_pb.tex}
\input{terms/sampleselectionbias_ac.tex}
\input{terms/semisupervised_mm.tex} 
\input{terms/standardizationandnormalisation_sm.tex}
\input{terms/structuralriskminimization_maf.tex}
\input{terms/syntheticfeatures_fcm.tex}
\input{terms/tensorprocessingunit_pi.tex}
\input{terms/transferlearning_jjd.tex}
%TODO

%%
% The back matter contains appendices, bibliographies, indices, glossaries, etc.

\backmatter



\bibliography{terms/featureselection_ab,terms/classification_cg,terms/empiricalriskminimisation_nf,terms/structuralriskminimization_maf,terms/bayesianmodels_kj,terms/neuralnetwork_bp,terms/roccurves_pb,terms/dimensionalityreduction_sc,terms/semisupervised_mm,terms/longshorttermmemory_nm,terms/regularisationofmodels_ja,terms/transferlearning_jjd,terms/sampleselectionbias_ac,terms/noiseindatasets_is,terms/onlinelearning_df,terms/crossvalidation_lmd,terms/confusionmatrix_df,terms/activationfunctions_km,terms/syntheticfeatures_fcm,terms/ensemblemethods_dv,terms/convolution_gebs,terms/evaluationmethods_ae,terms/generativemodels_pm,terms/hyperparameters_nm,terms/conceptdrift_mf,terms/standardizationandnormalisation_sm,terms/lossfunctions_ag,terms/tensorprocessingunit_pi} %TODO

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