project/templates/about/tutorial.html
branch2011
changeset 449 50770620ea7f
parent 448 7167b896d8de
child 460 4e50c25edb04
child 472 c8068bc1d7c3
--- a/project/templates/about/tutorial.html	Sat Nov 19 13:26:28 2011 +0530
+++ b/project/templates/about/tutorial.html	Thu Nov 24 09:29:05 2011 +0530
@@ -1,6 +1,46 @@
 {% extends "base.html" %}
 {% block content %}
-<h1>Tutorials</h1>
+<h1 class="title">SciPy.in 2011 Tutorial Schedule</h1>
+
+<h2 id="sec-1">Day 3 </h2>
+
+
+<table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides">
+<caption></caption>
+<colgroup><col class="right" /><col class="left" /><col class="left" />
+</colgroup>
+<thead>
+<tr><th scope="col" class="right">Time</th><th scope="col" class="left">Speaker</th><th scope="col" class="left">Title</th></tr>
+</thead>
+<tbody>
+<tr><td class="right">09:00-11:00</td><td class="left">Jarror Millman</td><td class="left"><a href="#sec2.1" >Gig/Github + NumPy/SciPy/MPL basics</a></td></tr>
+<tr><td class="right">11:00-13:00</td><td class="left">Emmanuelle Gouillart</td><td class="left"><a href="#sec2.2">Image processing using NumPy, SciPy and scikits-image</a></td></tr>
+<tr><td class="right">13:00-14:00</td><td class="left"></td><td class="left">Lunch</td></tr>
+<tr><td class="right">14:00-16:00</td><td class="left">Gael Varoquaux</td><td class="left"><a href="#sec2.3">Machine learning with scikit-learn</a></td></tr>
+<tr><td class="right">16:00-18:00</td><td class="left">Mateusz Paprocki</td><td class="left"><a href="#sec2.4">SymPy</a></td></tr>
+</tbody>
+</table>
+
+<h2 id="sec-2">Day 4 </h2>
+
+
+<table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides">
+<caption></caption>
+<colgroup><col class="right" /><col class="left" /><col class="left" />
+</colgroup>
+<thead>
+<tr><th scope="col" class="right">Time</th><th scope="col" class="left">Speaker</th><th scope="col" class="left">Title</th></tr>
+</thead>
+<tbody>
+<tr><td class="right">09:00-11:00</td><td class="left">Ole Nielsen</td><td class="left"><a href="#sec2.5">Mapping and Geoprocessing with Python</a></td></tr>
+<tr><td class="right">11:00-13:00</td><td class="left">Eric Jones</td><td class="left"><a href="#sec2.6">Traits + Traits UI</a></td></tr>
+<tr><td class="right">13:00-14:00</td><td class="left"></td><td class="left">Lunch</td></tr>
+<tr><td class="right">14:00-16:00</td><td class="left">Prabhu Ramachandran and Gael Varoquaux</td><td class="left"><a href="#sec2.7">Mayavi for 3D visualization</a></td></tr>
+<tr><td class="right">16:00-17:00</td><td class="left">Puneeth Chaganti</td><td class="left"><a href="#sec2.8">Sage introduction/tutorial</a></td></tr>
+<tr><td class="right">17:00-18:00</td><td class="left">Pankaj Pandey and Prabhu Ramachandran</td><td class="left"><a href="#sec2.9">An introduction to Cython</a></td></tr>
+</tbody>
+</table>
+<br/><br/>
 
 <h2 id="sec-1"><span class="section-number-3"></span>Intended audience </h2>
 
@@ -38,7 +78,7 @@
 
 
 
-<h3>Jarrod Millman, Git/Github + NumPy/SciPy/MPL basics (2 hrs)</h3>
+<h3 id="sec2.1">Jarrod Millman, Git/Github + NumPy/SciPy/MPL basics (2 hrs)</h3>
 <ul>
 	<li>Git/Github</li>
 	<li>NumPy and SciPy basics along with the most important Matplotlib commands.
@@ -48,7 +88,7 @@
 
 
 
-<h3>Emmanuelle Gouillart, Image processing using NumPy, SciPy and scikits-image (2 hrs)</h3>
+<h3 id="sec2.2">Emmanuelle Gouillart, Image processing using NumPy, SciPy and scikits-image (2 hrs)</h3>
 <ul>
 	<li>This tutorial will show a bag of basic recipes in order to efficiently
 manipulate and process images in the form of NumPy arrays.
@@ -81,7 +121,7 @@
 </ul>
 
 
-<h3>Gael Varoquaux,   Machine learning with scikit-learn  (2 hrs)</h3>
+<h3 id="sec2.3">Gael Varoquaux,   Machine learning with scikit-learn  (2 hrs)</h3>
 <ul>
 	<li>
 	Introduction to machine learning and statistical data processing with the
@@ -112,115 +152,7 @@
 	</li>
 </ul>
 
-<h3>Ole Nielsen: Mapping and Geoprocessing with Python (2 hrs)</h3>
-<ul>
-	<li>
-	Putting information on a map and analyzing spatial data are fundamental to a 
-	wide range of areas such as navigation, working with climate or geological data, 
-	disaster management, presentation of modelling results, demographics, social networking etc.
-	</li>
-	<li>
-	This tutorial will give a practical introduction to tools and techniques 
-	available for processing spatial information and, through a few hands-on 
-	exercises, give the participants a sense of how to manipulate and visualise 
-	spatial data using Python. Topics covered include reading and writing 
-	of important data formats for both raster and vector data, looking at the layers, 
-	awareness of issues with datums and projections, calculating centroids of polygons, 
-	calculation of distance between points on the surface of Earth, interpolation from raster 
-	grids to points etc. The tutorial has been developed for Ubuntu Linux and will provide source code, 
-	tests and data for this platform. However, the content and messages should be general and apply to any platform.
-	</li>
-	<li>
-	I assume that participants know how to write and run 
-	Python scripts and would suggest you install qgis as well as 
-	the python dependencies numpy, matplotlib and gdal on your 
-	laptop. I don't assume any previous knowledge of mapping or Geographic Information Systems (GIS).		
-	</li>
-	<li>
-	If you have some spatial data you want to manipulate in Python feel free to bring it along and grab me during a lunch break.
-	</li>
-</ul>
-
-
-<h3>Eric Jones/Puneeth/Pankaj: Traits + Traits UI (2 hrs)</h3> 
-<ul>
-	<li>
-	Enthought’s traits package provides for a powerful object model which 
-	provides a host of useful functionality with a clean and expressive syntax.  
-	It is an open source library and forms the basis of the Enthought Tool Suite and many of 
-	Enthought’s internal commercial projects.  In this tutorial we will cover the basics of using 
-	Traits along with the UI library TraitsUI which makes it very easy to build powerful and 
-	interactive, user interfaces using Traits.
-	</li>
-</ul>
-
-
-<h3>Prabhu Ramachandran and Gael Varoquaux, Mayavi for 3D visualization (2 hrs)</h3>
-<ul>
-	<li>
-	At the end of this tutorial attendees will learn how to visualize numpy
-	arrays using Mayavi's mlab interface.  They will also learn enough about
-	mayavi to be able to create their own simple datasets and visualize
-	them.  If this tutorial follows one on traits, then attendees will learn
-	how easy it is to embed 3D visualization in their own application UIs
-	(provided they are written in wxPython or PyQt).
-	</li>
-	<li>
-	In this tutorial, we first provide a rapid overview of Mayavi_ and its
-	features.  We then move on to using Mayavi via IPython_ and mlab.  This
-	is done in a hands-on fashion and introduces the audience to visualizing
-	numpy arrays and the basic mayavi visualization pipeline.  We then
-	introduce the audience to the basic objects and data sources used in
-	Mayavi.  We end with an example of creating custom dialogs using Traits
-	and embedding 3D visualization in these dialogs with Mayavi.
-	</li>
-	<li>
-	Packages required
-		<ul>
-			<li><a href="http://code.enthought.com/projects/mayavi">Mayavi</a></li>
-			<li><a href="http://ipython.scipy.org">IPython</a></li>
-			<li><a href="http://code.enthought.com/projects/traits">Traits</a></li>
-			<li>numpy, scipy</li>
-		</ul>
-	</li>
-</ul>
-
-<h3>Pankaj Pandey and Prabhu Ramachandran, An introduction to Cython (1 hrs)</h3>
-<ul>
-	<li>
-	At some level, Cython (http://www.cython.org) can be thought of a Python to C compiler.  
-	It allows someone to write extension modules in a language very similar to Python and 
-	therefore makes it rather easy to write C-extensions.  In this tutorial we will cover 
-	the basics of building extension modules with Cython.
-	</li>
-	<li>
-		Package requirements: You will require to have Cython, the 
-		Python development headers and a working C-compiler to run the hands-on exercises.
-	</li>
-</ul>
-
-<h3>Puneeth Chaganti, Sage introduction/tutorial: (1 hr)</h3>
-<ul>
-	<li>This tutorial will feature a demonstration and a brief review of some of the capabilities of the <a href="http://www.sagemath.org">Sage notebook</a>.</li>
-	<li>A rough schedule of the talk would be as follows:
-		<ul>
-			<li>Introduction</li>
-			<li>Starting the server</li>
-			<li>The UI</li>
-			<li>Getting Help</li>
-			<li>Overview of what's available in Sage
-				<ul>
-					<li>Basic Algebra</li>
-					<li>Basic Calculus</li>
-					<li>Basic Plotting</li>
-				</ul>
-	</li>
-		</ul>
-	</li>
-</ul>
-
-
-<h3>Mateusz Paprocki,  SymPy (2 hrs)</h3>
+<h3 id="sec2.4">Mateusz Paprocki,  SymPy (2 hrs)</h3>
 <ul>
 	<li>
 	SymPy is a pure Python library for symbolic mathematics. It aims to become a
@@ -263,4 +195,112 @@
 	</li>
 </ul>
 
+<h3 id="sec2.5">Ole Nielsen: Mapping and Geoprocessing with Python (2 hrs)</h3>
+<ul>
+	<li>
+	Putting information on a map and analyzing spatial data are fundamental to a 
+	wide range of areas such as navigation, working with climate or geological data, 
+	disaster management, presentation of modelling results, demographics, social networking etc.
+	</li>
+	<li>
+	This tutorial will give a practical introduction to tools and techniques 
+	available for processing spatial information and, through a few hands-on 
+	exercises, give the participants a sense of how to manipulate and visualise 
+	spatial data using Python. Topics covered include reading and writing 
+	of important data formats for both raster and vector data, looking at the layers, 
+	awareness of issues with datums and projections, calculating centroids of polygons, 
+	calculation of distance between points on the surface of Earth, interpolation from raster 
+	grids to points etc. The tutorial has been developed for Ubuntu Linux and will provide source code, 
+	tests and data for this platform. However, the content and messages should be general and apply to any platform.
+	</li>
+	<li>
+	I assume that participants know how to write and run 
+	Python scripts and would suggest you install qgis as well as 
+	the python dependencies numpy, matplotlib and gdal on your 
+	laptop. I don't assume any previous knowledge of mapping or Geographic Information Systems (GIS).		
+	</li>
+	<li>
+	If you have some spatial data you want to manipulate in Python feel free to bring it along and grab me during a lunch break.
+	</li>
+</ul>
+
+
+<h3 id="sec2.6">Eric Jones: Traits + Traits UI (2 hrs)</h3> 
+<ul>
+	<li>
+	Enthought’s traits package provides for a powerful object model which 
+	provides a host of useful functionality with a clean and expressive syntax.  
+	It is an open source library and forms the basis of the Enthought Tool Suite and many of 
+	Enthought’s internal commercial projects.  In this tutorial we will cover the basics of using 
+	Traits along with the UI library TraitsUI which makes it very easy to build powerful and 
+	interactive, user interfaces using Traits.
+	</li>
+</ul>
+
+
+<h3 id="sec2.7">Prabhu Ramachandran and Gael Varoquaux, Mayavi for 3D visualization (2 hrs)</h3>
+<ul>
+	<li>
+	At the end of this tutorial attendees will learn how to visualize numpy
+	arrays using Mayavi's mlab interface.  They will also learn enough about
+	mayavi to be able to create their own simple datasets and visualize
+	them.  If this tutorial follows one on traits, then attendees will learn
+	how easy it is to embed 3D visualization in their own application UIs
+	(provided they are written in wxPython or PyQt).
+	</li>
+	<li>
+	In this tutorial, we first provide a rapid overview of Mayavi_ and its
+	features.  We then move on to using Mayavi via IPython_ and mlab.  This
+	is done in a hands-on fashion and introduces the audience to visualizing
+	numpy arrays and the basic mayavi visualization pipeline.  We then
+	introduce the audience to the basic objects and data sources used in
+	Mayavi.  We end with an example of creating custom dialogs using Traits
+	and embedding 3D visualization in these dialogs with Mayavi.
+	</li>
+	<li>
+	Packages required
+		<ul>
+			<li><a href="http://code.enthought.com/projects/mayavi">Mayavi</a></li>
+			<li><a href="http://ipython.scipy.org">IPython</a></li>
+			<li><a href="http://code.enthought.com/projects/traits">Traits</a></li>
+			<li>numpy, scipy</li>
+		</ul>
+	</li>
+</ul>
+
+<h3 id="sec2.8">Puneeth Chaganti, Sage introduction/tutorial: (1 hr)</h3>
+<ul>
+	<li>This tutorial will feature a demonstration and a brief review of some of the capabilities of the <a href="http://www.sagemath.org">Sage notebook</a>.</li>
+	<li>A rough schedule of the talk would be as follows:
+		<ul>
+			<li>Introduction</li>
+			<li>Starting the server</li>
+			<li>The UI</li>
+			<li>Getting Help</li>
+			<li>Overview of what's available in Sage
+				<ul>
+					<li>Basic Algebra</li>
+					<li>Basic Calculus</li>
+					<li>Basic Plotting</li>
+				</ul>
+	</li>
+		</ul>
+	</li>
+</ul>
+
+<h3 id="sec2.9">Pankaj Pandey and Prabhu Ramachandran, An introduction to Cython (1 hrs)</h3>
+<ul>
+	<li>
+	At some level, Cython (http://www.cython.org) can be thought of a Python to C compiler.  
+	It allows someone to write extension modules in a language very similar to Python and 
+	therefore makes it rather easy to write C-extensions.  In this tutorial we will cover 
+	the basics of building extension modules with Cython.
+	</li>
+	<li>
+		Package requirements: You will require to have Cython, the 
+		Python development headers and a working C-compiler to run the hands-on exercises.
+	</li>
+</ul>
+
+
 {% endblock content %}