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mhjensen
2018-11-28 22:31:38 +01:00
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doc/pub/summary/html/._summary-bs000.html
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<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">"What did I learn in school this year":"https://www.youtube.com/watch?v=ZTxmDV_njsc"</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Linear algebra and eigenvalue problems, chapters 6.1-6.5 and 7.1-7.5</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Additional learning outcomes</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
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<!-- author(s): Morten Hjorth-Jensen Email morten.hjorth-jensen@fys.uio.no -->
<center>
<b>Morten Hjorth-Jensen Email morten.hjorth-jensen@fys.uio.no</b> [1, 2]
</center>
<p>
<!-- institution(s) -->
<center>[1] <b>Department of Physics and Center of Mathematics for Applications, University of Oslo</b></center>
<center>[2] <b>National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Nov 28, 2018</h4></center> <!-- date -->
<br>
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<p><a href="._summary-bs001.html" class="btn btn-primary btn-lg">Read &raquo;</a></p>
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<li><a href="._summary-bs005.html">6</a></li>
<li><a href="._summary-bs006.html">7</a></li>
<li><a href="._summary-bs007.html">8</a></li>
<li><a href="._summary-bs008.html">9</a></li>
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<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2018, Morten Hjorth-Jensen Email morten.hjorth-jensen@fys.uio.no. Released under CC Attribution-NonCommercial 4.0 license
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doc/pub/summary/html/._summary-bs001.html
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<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">"What did I learn in school this year":"https://www.youtube.com/watch?v=ZTxmDV_njsc"</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Linear algebra and eigenvalue problems, chapters 6.1-6.5 and 7.1-7.5</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Additional learning outcomes</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
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<h2 id="___sec0" class="anchor">What? Me worry? No final exam in this course! </h2>
<br /><br /><center><p><img src="figures/exam1.jpeg" align="bottom" width=500></p></center><br /><br />
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doc/pub/summary/html/._summary-bs002.html
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<title>Summary of course</title>
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<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
<!-- navigation toc: --> <li><a href="#___sec1" style="font-size: 80%;">"What did I learn in school this year":"https://www.youtube.com/watch?v=ZTxmDV_njsc"</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Linear algebra and eigenvalue problems, chapters 6.1-6.5 and 7.1-7.5</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Additional learning outcomes</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
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<p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p> <!-- add vertical space -->
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<h2 id="___sec1" class="anchor"><a href="https://www.youtube.com/watch?v=ZTxmDV_njsc" target="_self">What did I learn in school this year</a> </h2>
<p>
<a href="http://hplgit.github.io/edu/py_vs_m/computing_competence.html" target="_self">Our ideal about knowledge on computational science</a>
<p>
Does that match the experiences you have made this semester?
<br /><br /><center><p><img src="figures/exam2.jpg" align="bottom" width=500></p></center><br /><br />
<p>
<p>
<!-- navigation buttons at the bottom of the page -->
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<li><a href="._summary-bs006.html">7</a></li>
<li><a href="._summary-bs007.html">8</a></li>
<li><a href="._summary-bs008.html">9</a></li>
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doc/pub/summary/html/._summary-bs003.html
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<title>Summary of course</title>
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<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
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<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
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<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">"What did I learn in school this year":"https://www.youtube.com/watch?v=ZTxmDV_njsc"</a></li>
<!-- navigation toc: --> <li><a href="#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Linear algebra and eigenvalue problems, chapters 6.1-6.5 and 7.1-7.5</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Additional learning outcomes</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
</ul>
</li>
</ul>
</div>
</div>
</div> <!-- end of navigation bar -->
<div class="container">
<p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p> <!-- add vertical space -->
<a name="part0003"></a>
<!-- !split -->
<h2 id="___sec2" class="anchor">Topics we have covered this year </h2>
<ul>
<li></li>
<li> </li>
<li> </li>
<li></li>
</ul>
<p>
<!-- navigation buttons at the bottom of the page -->
<ul class="pagination">
<li><a href="._summary-bs002.html">&laquo;</a></li>
<li><a href="._summary-bs000.html">1</a></li>
<li><a href="._summary-bs001.html">2</a></li>
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('"What did I learn in school this '
'year":"https://www.youtube.com/watch?v=ZTxmDV_njsc"',
2,
None,
'___sec1'),
('Topics we have covered this year', 2, None, '___sec2'),
('Linear algebra and eigenvalue problems, chapters 6.1-6.5 and '
'7.1-7.5',
2,
None,
'___sec3'),
('Learning outcomes and overarching aims of this course',
2,
None,
'___sec4'),
('Additional learning outcomes', 2, None, '___sec5'),
('Other courses on Data science and Machine Learning at UiO',
2,
None,
'___sec6'),
('Best wishes to you all and thanks so much for your heroic '
'efforts this semester',
2,
None,
'___sec7')]}
end of tocinfo -->
<body>
<!-- Bootstrap navigation bar -->
<div class="navbar navbar-default navbar-fixed-top">
<div class="navbar-header">
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
</div>
<div class="navbar-collapse collapse navbar-responsive-collapse">
<ul class="nav navbar-nav navbar-right">
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
<ul class="dropdown-menu">
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">"What did I learn in school this year":"https://www.youtube.com/watch?v=ZTxmDV_njsc"</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Linear algebra and eigenvalue problems, chapters 6.1-6.5 and 7.1-7.5</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Additional learning outcomes</a></li>
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="#___sec7" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
</ul>
</li>
</ul>
</div>
</div>
</div> <!-- end of navigation bar -->
<div class="container">
<p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p> <!-- add vertical space -->
<a name="part0008"></a>
<!-- !split -->
<h2 id="___sec7" class="anchor">Best wishes to you all and thanks so much for your heroic efforts this semester </h2>
<p>
<br /><br /><center><p><img src="figures/Nebbdyr2.png" align="bottom" width=500></p></center><br /><br />
<p>
<p>
<!-- navigation buttons at the bottom of the page -->
<ul class="pagination">
<li><a href="._summary-bs007.html">&laquo;</a></li>
<li><a href="._summary-bs000.html">1</a></li>
<li><a href="._summary-bs001.html">2</a></li>
<li><a href="._summary-bs002.html">3</a></li>
<li><a href="._summary-bs003.html">4</a></li>
<li><a href="._summary-bs004.html">5</a></li>
<li><a href="._summary-bs005.html">6</a></li>
<li><a href="._summary-bs006.html">7</a></li>
<li><a href="._summary-bs007.html">8</a></li>
<li class="active"><a href="._summary-bs008.html">9</a></li>
</ul>
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</div> <!-- end container -->
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<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
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<footer>
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</footer>
-->
<center style="font-size:80%">
<!-- copyright only on the titlepage -->
</center>
</body>
</html>
doc/src/Summary/clean.sh
Executable
+3
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@@ -0,0 +1,3 @@
#!/bin/sh
doconce clean
rm -rf *.pdf *.tex ipynb*.tar.gz *.html ._*.html *~ reveal.js Trash README.txt
doc/src/Summary/figures/Nebbdyr2.pdf
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doc/src/Summary/make.sh
Executable
+95
View File
@@ -0,0 +1,95 @@
#!/bin/sh
set -x
function system {
"$@"
if [ $? -ne 0 ]; then
echo "make.sh: unsuccessful command $@"
echo "abort!"
exit 1
fi
}
if [ $# -eq 0 ]; then
echo 'bash make.sh slides1|slides2'
exit 1
fi
name=$1
rm -f *.tar.gz
opt="--encoding=utf-8"
# Note: Makefile examples contain constructions like ${PROG} which
# looks like Mako constructions, but they are not. Use --no_mako
# to turn off Mako processing.
opt="--no_mako"
rm -f *.aux
html=${name}-reveal
system doconce format html $name --pygments_html_style=perldoc --keep_pygments_html_bg --html_links_in_new_window --html_output=$html $opt
system doconce slides_html $html reveal --html_slide_theme=beige
# Plain HTML documents
html=${name}-solarized
system doconce format html $name --pygments_html_style=perldoc --html_style=solarized3 --html_links_in_new_window --html_output=$html $opt
system doconce split_html $html.html --method=space10
html=${name}
system doconce format html $name --pygments_html_style=default --html_style=bloodish --html_links_in_new_window --html_output=$html $opt
system doconce split_html $html.html --method=space10
# Bootstrap style
html=${name}-bs
system doconce format html $name --html_style=bootstrap --pygments_html_style=default --html_admon=bootstrap_panel --html_output=$html $opt
system doconce split_html $html.html --method=split --pagination --nav_button=bottom
# IPython notebook
system doconce format ipynb $name $opt
# Ordinary plain LaTeX document
rm -f *.aux # important after beamer
system doconce format pdflatex $name --minted_latex_style=trac --latex_admon=paragraph $opt
system doconce ptex2tex $name envir=minted
# Add special packages
doconce subst "% Add user's preamble" "\g<1>\n\\usepackage{simplewick}" $name.tex
doconce replace 'section{' 'section*{' $name.tex
pdflatex -shell-escape $name
pdflatex -shell-escape $name
mv -f $name.pdf ${name}-minted.pdf
cp $name.tex ${name}-plain-minted.tex
# Publish
dest=../../pub
if [ ! -d $dest/$name ]; then
mkdir $dest/$name
mkdir $dest/$name/pdf
mkdir $dest/$name/html
mkdir $dest/$name/ipynb
fi
cp ${name}*.pdf $dest/$name/pdf
cp -r ${name}*.html ._${name}*.html reveal.js $dest/$name/html
# Figures: cannot just copy link, need to physically copy the files
if [ -d fig-${name} ]; then
if [ ! -d $dest/$name/html/fig-$name ]; then
mkdir $dest/$name/html/fig-$name
fi
cp -r fig-${name}/* $dest/$name/html/fig-$name
fi
cp ${name}.ipynb $dest/$name/ipynb
ipynb_tarfile=ipynb-${name}-src.tar.gz
if [ ! -f ${ipynb_tarfile} ]; then
cat > README.txt <<EOF
This IPython notebook ${name}.ipynb does not require any additional
programs.
EOF
tar czf ${ipynb_tarfile} README.txt
fi
cp ${ipynb_tarfile} $dest/$name/ipynb
doc/src/Summary/summary.do.txt
+63
View File
@@ -0,0 +1,63 @@
TITLE: Summary of course
AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} Email morten.hjorth-jensen@fys.uio.no at Department of Physics and Center of Mathematics for Applications, University of Oslo & National Superconducting Cyclotron Laboratory, Michigan State University
DATE: today
!split
===== What? Me worry? No final exam in this course! =====
FIGURE: [figures/exam1.jpeg, width=500 frac=0.6]
FIGURE: [figures/whatmeworry.jpeg, width=500 frac=0.6]
!split
===== "What did I learn in school this year":"https://www.youtube.com/watch?v=ZTxmDV_njsc" =====
"Our ideal about knowledge on computational science":"http://hplgit.github.io/edu/py_vs_m/computing_competence.html"
Does that match the experiences you have made this semester?
FIGURE: [figures/exam2.jpg, width=500 frac=0.7]
!split
===== Topics we have covered this year =====
*
*
*
*
!split
===== Linear algebra and eigenvalue problems, chapters 6.1-6.5 and 7.1-7.5 =====
!split
===== Learning outcomes and overarching aims of this course =====
!split
===== Additional learning outcomes =====
!bblock
!eblock
!split
===== Other courses on Data science and Machine Learning at UiO =====
!split
===== Best wishes to you all and thanks so much for your heroic efforts this semester =====
FIGURE: [figures/Nebbdyr2.png, width=500 frac=0.6]
doc/web/course.do.txt
+2 -1
View File
@@ -10,7 +10,7 @@ AUTHOR: "Morten Hjorth-Jensen":"http://mhjgit.github.io/info/doc/web/" at Depart
<%
pub_url = 'https://compphysics.github.io/MachineLearning/doc/pub'
published = ['Intro2Course', 'Introduction', 'How2ReadData', 'Linalg', 'Statistics', 'Regression', 'Splines', 'LogReg', 'NeuralNet', 'DimRed', 'DecisionTrees', 'svm', 'BM', 'Recurrent', 'Autoencoders', 'Reinforce', 'odenn', 'Bayesian', ]
published = ['Intro2Course', 'Introduction', 'How2ReadData', 'Linalg', 'Statistics', 'Regression', 'Splines', 'LogReg', 'NeuralNet', 'DimRed', 'DecisionTrees', 'svm', 'BM', 'Recurrent', 'Autoencoders', 'Reinforce', 'odenn', 'Bayesian', 'summary',]
chapters = {
'Intro2Course': 'Basic introduction to the course with schedule etc',
'Introduction': 'Introduction to Data Analysis and Machine Learning',
@@ -30,6 +30,7 @@ chapters = {
'Reinforce': 'Reinforcement Learning',
'odenn': 'Solving ordinary and partial differential equations with Neural Networks',
'Bayesian': 'Elements of Bayesian theory',
'summary': 'Summary',
}
%>
doc/web/course.html
+64 -34
View File
@@ -105,30 +105,31 @@ div { text-align: justify; text-justify: inter-word; }
None,
'___sec16'),
('Elements of Bayesian theory', 2, None, '___sec17'),
('Python and Scikit Learn, a short guide', 2, None, '___sec18'),
('Teach yourself C++', 2, None, '___sec19'),
('Projects and Exercises Fall 2018', 2, None, '___sec20'),
('First homework set, week 35', 3, None, '___sec21'),
('Second homework set, week 36', 3, None, '___sec22'),
('Project 1, Deadline October 1', 3, None, '___sec23'),
('Project 2, Deadline November 5', 3, None, '___sec24'),
('Project 3, Deadline December 14', 3, None, '___sec25'),
('Course content', 3, None, '___sec26'),
('Learning outcomes', 2, None, '___sec27'),
('Prerequisites', 2, None, '___sec28'),
('The course has two central parts', 2, None, '___sec29'),
('Summary', 2, None, '___sec18'),
('Python and Scikit Learn, a short guide', 2, None, '___sec19'),
('Teach yourself C++', 2, None, '___sec20'),
('Projects and Exercises Fall 2018', 2, None, '___sec21'),
('First homework set, week 35', 3, None, '___sec22'),
('Second homework set, week 36', 3, None, '___sec23'),
('Project 1, Deadline October 1', 3, None, '___sec24'),
('Project 2, Deadline November 5', 3, None, '___sec25'),
('Project 3, Deadline December 14', 3, None, '___sec26'),
('Course content', 3, None, '___sec27'),
('Learning outcomes', 2, None, '___sec28'),
('Prerequisites', 2, None, '___sec29'),
('The course has two central parts', 2, None, '___sec30'),
('Statistical analysis and optimization of data',
3,
None,
'___sec30'),
('Machine learning', 3, None, '___sec31'),
('Recommended textbooks', 2, None, '___sec32'),
'___sec31'),
('Machine learning', 3, None, '___sec32'),
('Recommended textbooks', 2, None, '___sec33'),
('"Other '
'textbooks":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks"',
2,
None,
'___sec33'),
('Teaching schedule Fall 2018', 2, None, '___sec34')]}
'___sec34'),
('Teaching schedule Fall 2018', 2, None, '___sec35')]}
end of tocinfo -->
<body>
@@ -713,9 +714,38 @@ formulas in HTML or ipython notebook files.
</ul>
<h2 id="___sec18">Summary </h2>
<ul>
<li> LaTeX PDF:</li>
<ul>
<li> For printing:</li>
<ul>
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/summary/pdf/summary-minted.pdf" target="_self">Standard one-page format</a></li>
</ul>
</ul>
<li> HTML:</li>
<ul>
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/summary/html/summary.html" target="_self">Plain html</a></li>
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/summary/html/summary-bs.html" target="_self">Bootstrap slide style, easy for reading on mobile devices</a></li>
</ul>
<li> Jupyter notebook:</li>
<ul>
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/summary/ipynb/summary.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<!-- !split -->
<h2 id="___sec18">Python and Scikit Learn, a short guide </h2>
<h2 id="___sec19">Python and Scikit Learn, a short guide </h2>
<ul>
<li> HTML format only:</li>
@@ -728,7 +758,7 @@ formulas in HTML or ipython notebook files.
<!-- !split -->
<h2 id="___sec19">Teach yourself C++ </h2>
<h2 id="___sec20">Teach yourself C++ </h2>
<ul>
<li> HTML format only:</li>
@@ -741,9 +771,9 @@ formulas in HTML or ipython notebook files.
<!-- !split -->
<h2 id="___sec20">Projects and Exercises Fall 2018 </h2>
<h2 id="___sec21">Projects and Exercises Fall 2018 </h2>
<h3 id="___sec21">First homework set, week 35 </h3>
<h3 id="___sec22">First homework set, week 35 </h3>
<ul>
<li> LaTeX and PDF:</li>
@@ -762,7 +792,7 @@ formulas in HTML or ipython notebook files.
</ul>
<h3 id="___sec22">Second homework set, week 36 </h3>
<h3 id="___sec23">Second homework set, week 36 </h3>
<ul>
<li> LaTeX and PDF:</li>
@@ -781,7 +811,7 @@ formulas in HTML or ipython notebook files.
</ul>
<h3 id="___sec23">Project 1, Deadline October 1 </h3>
<h3 id="___sec24">Project 1, Deadline October 1 </h3>
<ul>
<li> LaTeX and PDF:</li>
@@ -800,7 +830,7 @@ formulas in HTML or ipython notebook files.
</ul>
<h3 id="___sec24">Project 2, Deadline November 5 </h3>
<h3 id="___sec25">Project 2, Deadline November 5 </h3>
<ul>
<li> LaTeX and PDF:</li>
@@ -819,7 +849,7 @@ formulas in HTML or ipython notebook files.
</ul>
<h3 id="___sec25">Project 3, Deadline December 14 </h3>
<h3 id="___sec26">Project 3, Deadline December 14 </h3>
<ul>
<li> LaTeX and PDF:</li>
@@ -838,7 +868,7 @@ formulas in HTML or ipython notebook files.
</ul>
<h3 id="___sec26">Course content </h3>
<h3 id="___sec27">Course content </h3>
<p>
Probability theory and statistical methods play a central role in science. Nowadays we are
@@ -857,7 +887,7 @@ tools of probability theory, the aim of this course is to expose you to central
This course covers thus topics like Monte Carlo methods and Markov chains, Bayesian statistics, error estimates, various linear methods, optimization of data and error analysis and central algorithms in machine learning.
The course has several numerical projects and numerical exercises that are meant to illustrate the theory.
<h2 id="___sec27">Learning outcomes </h2>
<h2 id="___sec28">Learning outcomes </h2>
<p>
The course introduces a variety of central algorithms and methods
@@ -874,19 +904,19 @@ essential for studies of data analysis and machine learning. The course is proje
<li> Work on numerical projects to illustrate the theory. The projects play a central role and students are expected to know modern programming languages like Python or C++.</li>
</ul>
<h2 id="___sec28">Prerequisites </h2>
<h2 id="___sec29">Prerequisites </h2>
<p>
Basic knowledge in programming and numerics. Required courses are the equivalents to the University of Oslo mathematics courses MAT1100, MAT1110, MAT1120 and at least one of the corresponding computing and programming courses INF1000/INF1110 or MAT-INF1100/MAT-INF1100L/BIOS1100/KJM-INF1xxx.
<h2 id="___sec29">The course has two central parts </h2>
<h2 id="___sec30">The course has two central parts </h2>
<ol>
<li> Statistical analysis and optimization of data</li>
<li> Machine learning</li>
</ol>
<h3 id="___sec30">Statistical analysis and optimization of data </h3>
<h3 id="___sec31">Statistical analysis and optimization of data </h3>
<p>
The following topics will be covered
@@ -903,7 +933,7 @@ The following topics will be covered
<li> Practical optimization using Singular-value decomposition and least squares for parameterizing data.</li>
</ul>
<h3 id="___sec31">Machine learning </h3>
<h3 id="___sec32">Machine learning </h3>
<p>
The following topics will be covered
@@ -919,14 +949,14 @@ The following topics will be covered
All the above topics will be supported by examples, hands-on exercises and project work.
<h2 id="___sec32">Recommended textbooks </h2>
<h2 id="___sec33">Recommended textbooks </h2>
<ul>
<li> <a href="https://www.springer.com/gp/book/9780387848570" target="_self">Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer</a></li>
<li> <a href="http://shop.oreilly.com/product/0636920052289.do" target="_self">Aurelien Geron, Hands&#8209;On Machine Learning with Scikit&#8209;Learn and TensorFlow, O'Reilly</a></li>
</ul>
<h2 id="___sec33"><a href="https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" target="_self">Other textbooks</a> </h2>
<h2 id="___sec34"><a href="https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" target="_self">Other textbooks</a> </h2>
<p>
<b>General learning book on statistical analysis</b>:
@@ -948,7 +978,7 @@ All the above topics will be supported by examples, hands-on exercises and proje
<!-- !split -->
<h2 id="___sec34">Teaching schedule Fall 2018 </h2>
<h2 id="___sec35">Teaching schedule Fall 2018 </h2>
<p>
Acronyms for textbooks and references to chapter