An awesome conference by an awesome software Rapid Miner remains one of the leading enterprise grade open source software , that can help you do a lot of things including flow driven data modeling ,web mining ,web crawling etc which even other software cant.
Mining Machine 2 Machine Data (Katharina Morik, TU Dortmund University)
Handling Big Data (Andras Benczur, MTA SZTAKI)
Introduction of RapidAnalytics at Telenor (Telenor and United Consult)
Here is a list of complete program
Training / Workshop 1
Training / Workshop 2
09:00 – 10:30
Ingo Mierswa (Rapid-I)Resource-aware Data Mining or M2M Mining (Invited Talk)
Data Mining for the Masses: A New Textbook on Data Mining for Everyone
Matthew North (Washington & Jefferson College)
Matthew North presents his new book “Data Mining for the Masses” introducing data mining to a broader audience and making use of RapidMiner for practical data mining problems.
Did you miss last years’ game show “Who wants to be a data miner?”? Use RapidMiner for problems it was never created for and beat the time and other contestants!
Get some Coffee for free – Writing Operators with RapidMiner Beans
Christian Bockermann, Hendrik Blom (TU Dortmund)
Meta-Modeling Execution Times of RapidMiner operators
Matija Piškorec, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute)
Social Event (Conference Dinner)
Social Event (Visit of Bar District)
Training: Basic Data Mining and Data Transformations
This is a short introductory training course for users who are not yet familiar with RapidMiner or only have a few experiences with RapidMiner so far. The topics of this training session include
Creating and handling RapidMiner repositories
Starting a new RapidMiner project
Operators and processes
Loading data from flat files
Storing data, processes, and results
Basic Data Transformations
Changing names and roles
Handling missing values
Changing value types by discretization and dichotimization
Normalization and standardization
Filtering examples and attributes
Scoring and Model Evaluation
Visualizing Model Performance
Training: Advanced Data Mining and Data Transformations
This is a short introductory training course for users who already know some basic concepts of RapidMiner and data mining and have already used the software before, for example in the first training on Tuesday. The topics of this training session include
Advanced Data Handling
Joins and Aggregations
Detection and removal of outliers
Control process execution
Remember process results
Recall process results
Using branches and conditions
Definition of macros
Usage of macros
Definition of log values
Clearing log tables
Transforming log tables to data
Development Workshop Part 1 and Part 2
Want to exchange ideas with the developers of RapidMiner? Or learn more tricks for developing own operators and extensions? During our development workshops on Tuesday and Friday, we will build small groups of developers each working on a small development project around RapidMiner. Beginners will get a comprehensive overview of the architecture of RapidMiner before making the first steps and learn how to write own operators. Advanced developers will form groups with our experienced developers, identify shortcomings of RapidMiner and develop a new extension which might be presented during the conference already. Unfinished work can be continued in the second workshop on Friday before results might be published on the Marketplace or can be taken home as a starting point for new custom operators.
One more addition to the GPU stack that adds up power when combined with CPU and GPUs. For numeric computing, it may be essential to have GPU- CPU mixed software as almost all hardware people now have offered GPU-CPU products. Maybe software companies can get inspired for new kind of GPU-CPU blade server software again.
But for “true” supercomputing applications, the SL390s G7 is the go-to server. Like its sibling, the SL390s comes with Xeon 5600 processors, but the option to pair the CPUs with up to three on-board NVIDIA “Fermi” 20-series GPUs puts a lot more floating point performance into this design. Customers can choose from either the M2050 or M2070 Tesla GPU modules, the only difference being the amount of graphics memory — 3 GB of GDDR5 for the M2050 versus 6 GB for the M2070. Each GPU module is served by its own PCIe Gen2 x16 channel in order to maximize bandwidth to the graphics chips. At the maximum configuration with all three Fermi GPUs and two Westmere CPUs, a single server delivers on the order of 1 teraflop of double precision performance. “So this is very much a server that has been designed for HPC,” said Turkel.
With GPUs on board, the SL390s fill out a 2U half-width tray, so up to four of these can be packed into a 4U SL6500 chassis. A CPU-only version is also available and takes up just half the space (half-width 1U), enabling twice as many Xeons to occupy the same chassis. This configuration will likely be the server of choice for the majority of HPC setups, given that GPGPU deployment is really just getting started. Pricing on the CPU-only model starts at $2,259.
, the ProLiant SL390s G7, provides more raw FLOPS per square inch than any server HP has delivered to date, and is the basis for the 2.4 petaflop TSUBAME 2.0 supercomputer currently being deployed at the Tokyo Institute of Technology.