mhjensen
278 lines
10 KiB
TeX
278 lines
10 KiB
TeX
%%
|
|
%% Automatically generated file from DocOnce source
|
|
%% (https://github.com/hplgit/doconce/)
|
|
%%
|
|
%%
|
|
% #ifdef PTEX2TEX_EXPLANATION
|
|
%%
|
|
%% The file follows the ptex2tex extended LaTeX format, see
|
|
%% ptex2tex: http://code.google.com/p/ptex2tex/
|
|
%%
|
|
%% Run
|
|
%% ptex2tex myfile
|
|
%% or
|
|
%% doconce ptex2tex myfile
|
|
%%
|
|
%% to turn myfile.p.tex into an ordinary LaTeX file myfile.tex.
|
|
%% (The ptex2tex program: http://code.google.com/p/ptex2tex)
|
|
%% Many preprocess options can be added to ptex2tex or doconce ptex2tex
|
|
%%
|
|
%% ptex2tex -DMINTED myfile
|
|
%% doconce ptex2tex myfile envir=minted
|
|
%%
|
|
%% ptex2tex will typeset code environments according to a global or local
|
|
%% .ptex2tex.cfg configure file. doconce ptex2tex will typeset code
|
|
%% according to options on the command line (just type doconce ptex2tex to
|
|
%% see examples). If doconce ptex2tex has envir=minted, it enables the
|
|
%% minted style without needing -DMINTED.
|
|
% #endif
|
|
|
|
% #define PREAMBLE
|
|
|
|
% #ifdef PREAMBLE
|
|
%-------------------- begin preamble ----------------------
|
|
|
|
\documentclass[%
|
|
oneside, % oneside: electronic viewing, twoside: printing
|
|
final, % draft: marks overfull hboxes, figures with paths
|
|
10pt]{article}
|
|
|
|
\listfiles % print all files needed to compile this document
|
|
|
|
\usepackage{relsize,makeidx,color,setspace,amsmath,amsfonts,amssymb}
|
|
\usepackage[table]{xcolor}
|
|
\usepackage{bm,ltablex,microtype}
|
|
|
|
\usepackage[pdftex]{graphicx}
|
|
|
|
\usepackage[T1]{fontenc}
|
|
%\usepackage[latin1]{inputenc}
|
|
\usepackage{ucs}
|
|
\usepackage[utf8x]{inputenc}
|
|
|
|
\usepackage{lmodern} % Latin Modern fonts derived from Computer Modern
|
|
|
|
% Hyperlinks in PDF:
|
|
\definecolor{linkcolor}{rgb}{0,0,0.4}
|
|
\usepackage{hyperref}
|
|
\hypersetup{
|
|
breaklinks=true,
|
|
colorlinks=true,
|
|
linkcolor=linkcolor,
|
|
urlcolor=linkcolor,
|
|
citecolor=black,
|
|
filecolor=black,
|
|
%filecolor=blue,
|
|
pdfmenubar=true,
|
|
pdftoolbar=true,
|
|
bookmarksdepth=3 % Uncomment (and tweak) for PDF bookmarks with more levels than the TOC
|
|
}
|
|
%\hyperbaseurl{} % hyperlinks are relative to this root
|
|
|
|
\setcounter{tocdepth}{2} % levels in table of contents
|
|
|
|
% --- fancyhdr package for fancy headers ---
|
|
\usepackage{fancyhdr}
|
|
\fancyhf{} % sets both header and footer to nothing
|
|
\renewcommand{\headrulewidth}{0pt}
|
|
\fancyfoot[LE,RO]{\thepage}
|
|
% Ensure copyright on titlepage (article style) and chapter pages (book style)
|
|
\fancypagestyle{plain}{
|
|
\fancyhf{}
|
|
\fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, "Data Analysis and Machine Learning FYS-STK3155/FYS4155":"http://www.uio.no/studier/emner/matnat/fys/FYS3155/index-eng.html". Released under CC Attribution-NonCommercial 4.0 license}}
|
|
% \renewcommand{\footrulewidth}{0mm}
|
|
\renewcommand{\headrulewidth}{0mm}
|
|
}
|
|
% Ensure copyright on titlepages with \thispagestyle{empty}
|
|
\fancypagestyle{empty}{
|
|
\fancyhf{}
|
|
\fancyfoot[C]{{\footnotesize \copyright\ 1999-2018, "Data Analysis and Machine Learning FYS-STK3155/FYS4155":"http://www.uio.no/studier/emner/matnat/fys/FYS3155/index-eng.html". Released under CC Attribution-NonCommercial 4.0 license}}
|
|
\renewcommand{\footrulewidth}{0mm}
|
|
\renewcommand{\headrulewidth}{0mm}
|
|
}
|
|
|
|
\pagestyle{fancy}
|
|
|
|
|
|
% prevent orhpans and widows
|
|
\clubpenalty = 10000
|
|
\widowpenalty = 10000
|
|
|
|
% --- end of standard preamble for documents ---
|
|
|
|
|
|
% insert custom LaTeX commands...
|
|
|
|
\raggedbottom
|
|
\makeindex
|
|
\usepackage[totoc]{idxlayout} % for index in the toc
|
|
\usepackage[nottoc]{tocbibind} % for references/bibliography in the toc
|
|
|
|
%-------------------- end preamble ----------------------
|
|
|
|
\begin{document}
|
|
|
|
% matching end for #ifdef PREAMBLE
|
|
% #endif
|
|
|
|
\newcommand{\exercisesection}[1]{\subsection*{#1}}
|
|
|
|
|
|
% ------------------- main content ----------------------
|
|
|
|
|
|
|
|
% ----------------- title -------------------------
|
|
|
|
\thispagestyle{empty}
|
|
|
|
\begin{center}
|
|
{\LARGE\bf
|
|
\begin{spacing}{1.25}
|
|
Project 1 on Machine Learning, deadline October 1
|
|
\end{spacing}
|
|
}
|
|
\end{center}
|
|
|
|
% ----------------- author(s) -------------------------
|
|
|
|
\begin{center}
|
|
{\bf \href{{http://www.uio.no/studier/emner/matnat/fys/FYS3155/index-eng.html}}{Data Analysis and Machine Learning FYS-STK3155/FYS4155}}
|
|
\end{center}
|
|
|
|
\begin{center}
|
|
% List of all institutions:
|
|
\centerline{{\small Department of Physics, University of Oslo, Norway}}
|
|
\end{center}
|
|
|
|
% ----------------- end author(s) -------------------------
|
|
|
|
% --- begin date ---
|
|
\begin{center}
|
|
May 2018
|
|
\end{center}
|
|
% --- end date ---
|
|
|
|
\vspace{1cm}
|
|
|
|
|
|
\subsection{Regression analysis and classification}
|
|
|
|
\paragraph{Introduction.}
|
|
\paragraph{Part a): The data.}
|
|
\subsection{Background literature}
|
|
|
|
|
|
|
|
|
|
\subsection{Introduction to numerical projects}
|
|
|
|
Here follows a brief recipe and recommendation on how to write a report for each
|
|
project.
|
|
|
|
\begin{itemize}
|
|
\item Give a short description of the nature of the problem and the eventual numerical methods you have used.
|
|
|
|
\item Describe the algorithm you have used and/or developed. Here you may find it convenient to use pseudocoding. In many cases you can describe the algorithm in the program itself.
|
|
|
|
\item Include the source code of your program. Comment your program properly.
|
|
|
|
\item If possible, try to find analytic solutions, or known limits in order to test your program when developing the code.
|
|
|
|
\item Include your results either in figure form or in a table. Remember to label your results. All tables and figures should have relevant captions and labels on the axes.
|
|
|
|
\item Try to evaluate the reliabilty and numerical stability/precision of your results. If possible, include a qualitative and/or quantitative discussion of the numerical stability, eventual loss of precision etc.
|
|
|
|
\item Try to give an interpretation of you results in your answers to the problems.
|
|
|
|
\item Critique: if possible include your comments and reflections about the exercise, whether you felt you learnt something, ideas for improvements and other thoughts you've made when solving the exercise. We wish to keep this course at the interactive level and your comments can help us improve it.
|
|
|
|
\item Try to establish a practice where you log your work at the computerlab. You may find such a logbook very handy at later stages in your work, especially when you don't properly remember what a previous test version of your program did. Here you could also record the time spent on solving the exercise, various algorithms you may have tested or other topics which you feel worthy of mentioning.
|
|
\end{itemize}
|
|
|
|
\noindent
|
|
\subsection{Format for electronic delivery of report and programs}
|
|
|
|
The preferred format for the report is a PDF file. You can also use DOC or postscript formats or as an ipython notebook file. As programming language we prefer that you choose between C/C++, Fortran2008 or Python. The following prescription should be followed when preparing the report:
|
|
|
|
\begin{itemize}
|
|
\item Use Devilry to hand in your projects, log in at \href{{http://devilry.ifi.uio.no}}{\nolinkurl{http://devilry.ifi.uio.no}} with your normal UiO username and password and choose either 'fysstk3155' or 'fysstk4155'. There you can load up the files within the deadline.
|
|
|
|
\item Upload \textbf{only} the report file! For the source code file(s) you have developed please provide us with your link to your github domain. The report file should include all of your discussions and a list of the codes you have developed. Do not include library files which are available at the course homepage, unless you have made specific changes to them.
|
|
|
|
\item In your git repository, please include a folder which contains selected results. These can be in the form of output from your code for a selected set of runs and input parameters.
|
|
|
|
\item In this and all later projects, you should include tests (for example unit tests) of your code(s).
|
|
|
|
\item Comments from us on your projects, approval or not, corrections to be made etc can be found under your Devilry domain and are only visible to you and the teachers of the course.
|
|
\end{itemize}
|
|
|
|
\noindent
|
|
Finally,
|
|
we encourage you to work two and two together. Optimal working groups consist of
|
|
2-3 students. You can then hand in a common report.
|
|
|
|
|
|
|
|
\subsection{Software and needed installations}
|
|
|
|
If you have Python installed (we recommend Python3) and you feel pretty familiar with installing different packages,
|
|
we recommend that you install the following Python packages via \textbf{pip} as
|
|
\begin{enumerate}
|
|
\item pip install numpy scipy matplotlib ipython scikit-learn tensorflow sympy pandas pillow
|
|
\end{enumerate}
|
|
|
|
\noindent
|
|
For Python3, replace \textbf{pip} with \textbf{pip3}.
|
|
|
|
See below for a discussion of \textbf{tensorflow} and \textbf{scikit-learn}.
|
|
|
|
For OSX users we recommend also, after having installed Xcode, to install \textbf{brew}. Brew allows
|
|
for a seamless installation of additional software via for example
|
|
\begin{enumerate}
|
|
\item brew install python3
|
|
\end{enumerate}
|
|
|
|
\noindent
|
|
For Linux users, with its variety of distributions like for example the widely popular Ubuntu distribution
|
|
you can use \textbf{pip} as well and simply install Python as
|
|
\begin{enumerate}
|
|
\item sudo apt-get install python3 (or python for python2.7)
|
|
\end{enumerate}
|
|
|
|
\noindent
|
|
etc etc.
|
|
|
|
If you don't want to install various Python packages with their dependencies separately, we recommend two widely used distrubutions which set up all relevant dependencies for Python, namely
|
|
\begin{enumerate}
|
|
\item \href{{https://docs.anaconda.com/}}{Anaconda} Anaconda is an open source distribution of the Python and R programming languages for large-scale data processing, predictive analytics, and scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system \textbf{conda}
|
|
|
|
\item \href{{https://www.enthought.com/product/canopy/}}{Enthought canopy} is a Python distribution for scientific and analytic computing distribution and analysis environment, available for free and under a commercial license.
|
|
\end{enumerate}
|
|
|
|
\noindent
|
|
Popular software packages written in Python for ML are
|
|
|
|
\begin{itemize}
|
|
\item \href{{http://scikit-learn.org/stable/}}{Scikit-learn},
|
|
|
|
\item \href{{https://www.tensorflow.org/}}{Tensorflow},
|
|
|
|
\item \href{{http://pytorch.org/}}{PyTorch} and
|
|
|
|
\item \href{{https://keras.io/}}{Keras}.
|
|
\end{itemize}
|
|
|
|
\noindent
|
|
These are all freely available at their respective GitHub sites. They
|
|
encompass communities of developers in the thousands or more. And the number
|
|
of code developers and contributors keeps increasing.
|
|
|
|
|
|
% ------------------- end of main content ---------------
|
|
|
|
% #ifdef PREAMBLE
|
|
\end{document}
|
|
% #endif
|
|
|