# HG changeset patch # User primal primal007@gmail.com # Date 1322647775 -19800 # Node ID 4be31211634aea66909258c940c0991c06f46b8a # Parent 4e50c25edb04e768e63cdc86a60cd4cb18b40da1 Changes in Conference Schedule diff -r 4e50c25edb04 -r 4be31211634a project/templates/about/tutorial.html --- a/project/templates/about/tutorial.html Wed Nov 30 13:25:05 2011 +0530 +++ b/project/templates/about/tutorial.html Wed Nov 30 15:39:35 2011 +0530 @@ -207,19 +207,19 @@ maps.

- T This tutorial will give a practical introduction to tools and techniques + This tutorial will give a practical introduction to tools and techniques available for processing spatial information and, through hands-on - exercises, give the participants a sense of how to manipulate spatial data - using Python. Depending on time, topics covered include reading and writing - of important data formats for both raster and vector data, looking at the + exercises, give the participants a sense of how to manipulate spatial data + using Python. Depending on time, topics covered include reading and writing + of important data formats for both raster and vector data, looking at the layers with qgis, awareness of issues with datums and projections, calculating area and centroids of polygons, performance enhancement using vector operations, numerical stability issues, 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 11.04/11.10 and - will provide source code, tests and data for this platform. However, the - content and messages should be general and apply to any self-respecting - platform. + between points on the surface of Earth, interpolation from raster grids to + points etc. The tutorial has been developed for Ubuntu Linux 11.04/11.10 and + will provide source code, tests and data for this platform. However, the + content and messages should be general and apply to any self-respecting + platform.

I assume that participants know how to write and run Python scripts and are @@ -228,9 +228,9 @@ Geographic Information Systems (GIS). The tutorial depends on the packages qgis and gdal-bin as well as the python dependencies python-numpy and python-gdal which are preloaded on the distributed live-DVD. The - tutorial material itself will be available in the Subversion repository - http://oles-tutorials.googlecode.com/svn/trunk/scipy2011 and also on a USB - stick that I will bring along. + tutorial material itself will be available in the + Subversion repository + and also on a usb stick that I will bring along.

If you have some spatial data you want to manipulate in Python feel free to diff -r 4e50c25edb04 -r 4be31211634a project/templates/talk/conf_schedule.html --- a/project/templates/talk/conf_schedule.html Wed Nov 30 13:25:05 2011 +0530 +++ b/project/templates/talk/conf_schedule.html Wed Nov 30 15:39:35 2011 +0530 @@ -24,11 +24,12 @@ 13:55-14:15Bala Subrahmanyam VaranasiSentiment Analysis 14:15-14:45Vishal KanaujiaExploiting the power of multicore for scientific computing in Python 14:45-14:55Lightning Talks -14:55-15:25Tea -14:25-15:55Jayneil DalalBuilding Embedded Systems for Image Processing using Python -15:55-16:25Kunal PuriSmoothed Particle Hydrodynamics with Python -16:25-16:45Nivedita DattaEncryptedly yours : Python & Cryptography -16:45-17:30GaelMachine learning as a tool for Neuroscience +14:55-15:25Tea Break +15:25-16:10Prabhu RamachandranInvited Talk +16:10-16:40Jayneil Dalal Building Embedded Systems for Image Processing using Python +16:40-17:10Kunal PuriSmoothed Particle Hydrodynamics with Python +17:10-17:30Nivedita DattaEncryptedly yours : Python & Cryptography + @@ -44,22 +45,20 @@ TimeSpeakerTitle -09:00-09:45Prabhu RamachandranInvited -09:45-10:05Mahendra NaikLarge amounts of data downloading and processing in python with facebook data as reference -10:05-10:15Lightning Talks +09:00-09:45GaelInvited Speaker: Machine learning as a tool for Neuroscience +09:45-10:15Kannan MoudgalyaInvited 10:15-10:45Tea 10:45-11:05Hrishikesh Deshpande Higher Order Statistics in Python 11:05-11:25Shubham ChakrabortyCombination of Python and Phoenix-M as a low cost substitute for PLC 11:25-12:10EmmanuelleInvited 12:10-13:10Lunch -13:10-13:55AsokanInvited -13:55-14:15Jaidev DeshpandeA Python Toolbox for the Hilbert-Huang Transform -14:15-14:45Chetan GiridharDiving in to Byte-code optimization in Python -14:45-14:55Lightning Talks -14:55-15:25Tea -15:25-16:05Ole NielsenInvited -16:05-16:35Kunal puriGPU Accelerated Computational Fluid Dynamics with Python -16:35-16:45Sachin ShindeReverse Engineering and python +13:10-13:30Mahendra NaikLarge amounts of data downloading and processing in python with facebook data as reference +13:30-14:10Ole NielsenInvited +14:10-14:30Jaidev DeshpandeA Python Toolbox for the Hilbert-Huang Transform +14:30-15:00Chetan GiridharDiving in to Byte-code optimization in Python +15:00-15:30Tea +15:305-16:00Kunal puriGPU Accelerated Computational Fluid Dynamics with Python +16:00-16:10Sachin ShindeReverse Engineering and python 16:10-16:40Jarrod MillmanInvited @@ -381,7 +380,7 @@ computational challenges that are well-known in large data analytics. The scipy stack, including Cython and scikit-learn, used with care, can provide a high-performance environment, matching dedicated solutions. I -will highlight how the *scikit-learn* performs efficient data analysis in +will highlight how the scikit-learn performs efficient data analysis in Python.