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Volume3.tex
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Volume3.tex
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\pdfminorversion=4
\documentclass[opener-c,labs,yellow,nociteref]{HJnewsiambook}
\newcommand{\given}{\!\mathrel{\big|}\!}
% See command.tex for all package imports, environments, and special commands.
\input{command}
\makeindex
\title{Volume 3\\ Modeling with Uncertainty and Data}
\author{Jeffrey Humpherys \& Tyler J.~Jarvis, managing editors}
\begin{document} % ============================================================
\newif\ifbyu
\byutrue
\byufalse % Create Public Labs; Comment for BYU Labs
\thispagestyle{empty} % Book cover and Front matter ---------------------------
\maketitle
\thispagestyle{empty}
\frontmatter
\include{contributors}
\begin{thepreface} % Preface --------------------------------------------------
This lab manual is designed to accompany the textbook \emph{Foundations of Applied Mathematics Volume 3: Modeling with Uncertainty and Data} by Humpherys and Jarvis.
The labs present various aspects of important machine learning algorithms.
The reader should be familiar with Python \cite{vanrossum2010python} and its NumPy \cite{oliphant2006guide,ascher2001numerical,oliphant2007python} and Matplotlib \cite{Hunter:2007} packages before attempting these labs.
See the Python Essentials manual for introductions to these topics.
\vfill
\copyright{This work is licensed under the Creative Commons Attribution 3.0 United States License.
You may copy, distribute, and display this copyrighted work only if you give credit to Dr.~J.~Humpherys.
All derivative works must include an attribution to Dr.~J.~Humpherys as the owner of this work as well as the web address to
\\
\centerline{\url{https://github.com/Foundations-of-Applied-Mathematics/Labs}}
\\
as the original source of this work.
\\
To view a copy of the Creative Commons Attribution 3.0 License, visit
\\
\centerline{\url{http://creativecommons.org/licenses/by/3.0/us/}}
or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA.}
\vfill
\centering\includegraphics[height=1.2cm]{by.pdf}
\vfill
\end{thepreface}
\setcounter{tocdepth}{1}
\tableofcontents
\mainmatter % LABS ============================================================
\ifbyu
\part{Labs} % BYU Volume 3 Labs ---------------------------------------------------
\subimport{./PythonEssentials/AdvancedNumpy/}{AdvancedNumpy}
\subimport{./DataScienceEssentials/Pandas1/}{Pandas1}
\subimport{./DataScienceEssentials/Pandas2/}{Pandas2}
\subimport{./DataScienceEssentials/Pandas3/}{Pandas3}
\subimport{./Volume3/InformationTheory/}{InformationTheory}
\subimport{./DataScienceEssentials/Pandas4/}{Pandas4}
\subimport{./Volume3/LSI_SkLearn/}{LSI-SkLearn}
\subimport{./DataScienceEssentials/DataCleaning/}{DataCleaning}
\subimport{./Volume3/RandomForest/}{RandomForest}
\subimport{./Volume3/KMeans/}{KMeans}
\subimport{./Volume3/LinearRegression/}{LinearRegression}
\subimport{./DataScienceEssentials/Parallel_Intro/}{parallel1}
\subimport{./Volume3/LogisticRegression/}{LogisticRegression}
% \subimport{./Volume3/NaiveBayes/}{NaiveBayes}
% \subimport{./DataScienceEssentials/Spark/}{spark}
% \subimport{./DataScienceEssentials/MPI/}{mpi}
% \subimport{./DataScienceEssentials/WebScraping/}{WebScraping}
% % \subimport{./DataScienceEssentials/WebCrawling/}{WebCrawling}
% \subimport{./Volume3/Metropolis/}{Metropolis}
% \subimport{./Volume3/Gibbs_LDA/}{LDA}
% \subimport{./Volume3/GMM/}{GMM}
% \subimport{./Volume3/HMM/}{HMM}
% \subimport{./Volume3/CDHMM/}{CDHMM}
% \subimport{./Volume3/KalmanFilter/}{KalmanFilter}
% \subimport{./Volume3/ARMA/}{ARMA}
% \subimport{./Volume3/NMF_Recommender/}{NMF_Recommender}
% \subimport{./Volume3/DeepLearningIntro/}{DeepLearningIntro}
% \subimport{./Volume3/RNN/}{rnn}
\else
\part{Labs} % Public Volume 3 Labs ---------------------------------------------------
\subimport{./Volume3/InformationTheory/}{InformationTheory}
\subimport{./Volume3/LSI_SkLearn/}{LSI-SkLearn}
\subimport{./Volume3/KMeans/}{KMeans}
\subimport{./Volume3/RandomForest/}{RandomForest}
\subimport{./Volume3/LinearRegression/}{LinearRegression}
\subimport{./Volume3/LogisticRegression/}{LogisticRegression}
\subimport{./Volume3/NaiveBayes/}{NaiveBayes}
% \subimport{./Volume3/DataAugmentation/}{DataAugmentation}
\subimport{./Volume3/Metropolis/}{Metropolis}
\subimport{./Volume3/Gibbs_LDA/}{LDA}
\subimport{./Volume3/GMM/}{GMM}
\subimport{./Volume3/HMM/}{HMM}
\subimport{./Volume3/CDHMM/}{CDHMM}
\subimport{./Volume3/KalmanFilter/}{KalmanFilter}
\subimport{./Volume3/ARMA/}{ARMA}
\subimport{./Volume3/NMF_Recommender/}{NMF_Recommender}
\subimport{./Volume3/DeepLearningIntro/}{DeepLearningIntro}
\subimport{./Volume3/RNN/}{rnn}
\fi
\part{Appendices}
\begin{appendices}
\subimport{./Appendices/NumpyVisualGuide/}{NumpyVisualGuide}
\subimport{./Appendices/MatplotlibCustomization/}{MatplotlibCustomization}
% \subimport{./Appendices/SklearnGuide/}{SklearnGuide}
\end{appendices}
% bibliography
\bibliographystyle{alpha}
\bibliography{references}
\end{document}