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\documentclass[a4paper, 12pt, english]{article}
\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage{listings}
\usepackage{xcolor}
\usepackage{hyperref}
\usepackage{multicol}
\usepackage{setspace}
\usepackage{graphicx}
% allow deeeep lists
\usepackage{enumitem}
\setlistdepth{9}
\setlist[itemize,1]{label=$\bullet$}
\setlist[itemize,2]{label=$\bullet$}
\setlist[itemize,3]{label=$\bullet$}
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\setlist[itemize,9]{label=$\bullet$}
\renewlist{itemize}{itemize}{9}
\setlist[enumerate,1]{label=$\arabic*.$}
\setlist[enumerate,2]{label=$\alph*.$}
\setlist[enumerate,3]{label=$\roman*.$}
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\renewlist{enumerate}{enumerate}{9}
\title{Intelligent World Informatics Lecture V\\ Final Project}
\author{Paul Lödige \\ Student ID: 37-229753 \\ paul.loedige@student.kit.edu}
\makeatletter
\newcommand*{\toccontents}{\@starttoc{toc}}
\makeatother
\begin{document}
\maketitle
\toccontents
\section{Assignment}%
\label{sec:Assignment}
\begin{itemize}
\item Define your own project
\begin{itemize}
\item Describe the task and the goal you would like to achieve
\item Experiment on any public dataset provided by Tensorflow:
\begin{itemize}
\item Full list: \url{https://www.tensorflow.org/datasets/catalog/overview}
\item Simple datasets: \url{https://www.tensorflow.org/api_docs/python/tf/keras/datasets}
\end{itemize}
\item Do one of the followings:
\begin{enumerate}
\item Apply two different deep learning techniques you learned from this class
\begin{itemize}
\item e.g.: Comparing Dense DNN vs RNN method on the same dataset (what pros and cons?)
\item e.g.: Combining CNN and RNN on a dataset (why the combination is preferable?)
\end{itemize}
\item Apply transfer learning with two different base models
\begin{itemize}
\item Explain the reasons why the base models are reasonable choices.
\item Survey on the internet with keywords
such as “best model for imagenet/cifar10/mnist”, “tensorflow pre-trained models”, etc,
to find the name of the model
\item Download the base model through tensorflow
\begin{itemize}
\item Just like in the code, simply change the name of the base model.
List of available base models in Tensorflow:
\begin{itemize}
\item \url{https://www.tensorflow.org/api_docs/python/tf/keras/applications}
\end{itemize}
\item Add layers, dropouts, use different learning rate, epoch, batch\_size, etc.
\end{itemize}
\end{itemize}
\end{enumerate}
\end{itemize}
\end{itemize}
\subsection{Additional Details}%
\label{sub:Additional Details}
\begin{itemize}
\item Write 1 $\sim 2$ page(s) (excluding the code) describing your project:
\begin{itemize}
\item Imagine the project as a kind of “mini research paper”
\item What is the problem? What is your motivation?
\item How are you solving them? What deep learning algorithms?
\item Outline the experiment and test on the dataset.
\item What are the results?
\begin{itemize}
\item Add at least 1 figure and insert your analysis
\end{itemize}
\item Attach the code at the end.
\item Include your name, affiliation, student number,
as well as your university e-mail address in case if we need to contact you for clarification
\item Put all the above in a single PDF and upload to ITC-LMS
\end{itemize}
\end{itemize}
\subsection{How the project is graded}%
\label{sub:How the project is graded}
\begin{itemize}
\item The purpose of the project is to make you familiar with machine learning experiments.
\begin{itemize}
\item Not intended to be a stressful project.
\begin{itemize}
\item So do not worry too much on achieving high accuracy, good parameter settings, etc
\item Make sure to keep it simple
\end{itemize}
\end{itemize}
\item What we would like to see:
\begin{itemize}
\item Clarity of the project description
\item Relevance between the problem and the chosen approaches
\item Appropriate input/output design and execution of the experiments
\item Proper evaluation methods, figures and tables
\item Easy to understand writings, informative comments on the code
\end{itemize}
\item Overall grade for this course : 70\% homeworks, 30\% final project
\begin{itemize}
\item Bonus points for helping each other on slack
\begin{itemize}
\item Feel free to discuss your final project on slack if you have troubles
\end{itemize}
\end{itemize}
\end{itemize}
\clearpage
%\section{Code}%
%\label{sec:Code}
%\definecolor{mGreen}{rgb}{0,0.6,0}
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%\definecolor{mPurple}{rgb}{0.58,0,0.82}
%\definecolor{backgroundColour}{rgb}{0.95,0.95,0.92}
%\lstset{
%language=C,
%backgroundcolor=\color{backgroundColour},
%commentstyle=\color{mGreen},
%keywordstyle=\color{magenta},
%numberstyle=\tiny\color{mGray},
%stringstyle=\color{mPurple},
%basicstyle=\ttfamily\scriptsize,
%breakatwhitespace=false,
%breaklines=true,
%captionpos=b,
%keepspaces=true,
%numbers=left,
%firstnumber=0,
%stepnumber=1,
%numbersep=5pt,
%showspaces=false,
%showstringspaces=false,
%showtabs=false,
%tabsize=2,
%literate={~}{{$\mathtt{\sim}$}}1
%}
%\lstset{literate=%
%{Ö}{{\"O}}1
%{Ä}{{\"A}}1
%{Ü}{{\"U}}1
%{ß}{{\ss}}2
%{ü}{{\"u}}1
%{ä}{{\"a}}1
%{ö}{{\"o}}1
%}
%\subsection{\texttt{vinput.c}}%
%\label{sub:vinput_c}
%\lstinputlisting{../Code/vinput.c}
%\clearpage
%\subsection{\texttt{vinput.h}}%
%\label{sub:vinput_h}
%\lstinputlisting{../Code/vinput.h}
%\clearpage
%\subsection{\texttt{vkbd.c}}%
%\label{sub:vkbd}
%\lstinputlisting{../Code/vkbd.c}
%\clearpage
%\section{Output}%
%\label{sec:Output}
%\subsection{Shell Script for compiling and running}%
%\label{sub:Shell Script for compiling and running}
%\includegraphics[width=\textwidth]{run_sh.png}
%\subsection{Terminal Screenshot}%
%\label{sub:Terminal Screenshot}
%\includegraphics[width=\textwidth]{executing_screenshot.png}
%\subsection{\texttt{output.txt}}%
%\label{sub:output_txt}
%\includegraphics[width=\textwidth]{output_txt.png}
\end{document}