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\begin{document}

%----------------------------------------------------------------
%Book cover and Front matter
\thispagestyle{empty}
\begin{center}
{\huge \bf Labs for Foundations of Applied Mathematics} \\
\vspace{5mm}
{\Large \bf Volume III: Modeling with
Uncertainty and Data}
\vspace{20mm}

\includegraphics[scale = .25]{Cover}
\end{center}
\frontmatter

\include{contributors}

%------------------------------------------------------------------
%The preface, which will presumably be longer in the future

\begin{thepreface}
This lab manual is designed to accompany the textbook \emph{Foundations of Applied Mathematics} by Humpherys and Jarvis.

\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/byuimpact/numerical_computing}}\\ 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.}

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\end{thepreface}
%-----------------------------------------------------------------

\setcounter{tocdepth}{1}
\tableofcontents

\mainmatter

\part{Measure Theory}
\subimport{./Python/SQL/}{DatabaseEssentials}
\subimport{./Python/AdvancedSQL/}{advanced_sql}
\subimport{./Python/pandas/}{pandas}
\subimport{./Python/PandasII/}{pandasII}

\part{Random Spaces and Variables}

\subimport{./Python/StateMachines/}{StateMachines}
\subimport{./Python/Scrapy/}{scraping}
\subimport{./Python/WebTechnology/}{WebTechnology}

\part{Distributions}

\part{Limit Theorems}
\subimport{./Labs/MPITrapezoidalRule/}{MPITrapezoidalRule}
\subimport{./Labs/MPICollectiveCommunication/}{MPICollectiveCommunication}


\part{Markov Processes}

\part{Poisson Distributions, Queues, and Renewal}
\subimport{./Python/MongoDB/}{MongoDB}

\part{Martingales and Diffusion}

\part{Information Theory}

\part{Multivariable Statistics}
\subimport{./Labs/PCA/}{PCA}
\subimport{./Labs/LSI/}{LSI}

\part{State Estimation}
\subimport{./Labs/KalmanFilter/}{kalman}
\subimport{./Labs/ProjectileTracking/}{projectiletracking}
\subimport{./Labs/HMMStateEstimation/}{hmmstates}
\subimport{./Labs/HMMNaturalLanguage/}{englishvowels}

\part{Time Series}

\part{Expectation Maximization}
\subimport{./Labs/HMMParameterEstimation/}{hmmtrain}
\subimport{./Labs/HMMRussian/}{russianalphabet}
\subimport{./Labs/CDHMM/}{cdhmm}
\subimport{./Labs/SpeechRecognition/}{speechrecognition}

\part{Bayesian Statistics I}
\subimport{./Labs/BayesianUpdate/}{bayesianupdate}
\subimport{./Labs/SearchAndRescue/}{bayesiansearch}

\part{Bayesian Statistics II}
\subimport{./Labs/Metropolis/}{metropolis}
\subimport{./Labs/IsingModel/}{isingmodel}
\subimport{./Labs/GibbsSampling/}{gibbs}
\subimport{./Labs/LDA/}{lda}

\part{Machine Learning I}
\subimport{./Labs/KMeans/}{kmeans}
\subimport{./Labs/GMM/}{gmm}
\subimport{./Labs/CrimeMapping/}{crimemapping}

\part{Machine Learning II}
\subimport{./Labs/CART/}{cart}
\subimport{./Labs/TitanicSurvival/}{randomforest}
\subimport{./Labs/KNNSVM/}{knnsvm}
\subimport{./Labs/ImageRecognition/}{imagerecognition}

\end{document}
