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RM Staff
RM Staff

Please vote for RapidMiner at KDNuggets 2016

Hi everybody,

It is this time of the year again and RapidMiner needs YOUR help! We give our best to provide you a feature-rich and easy-to-use predictive analytics platform - with most of its features being completely free!  So don't hesitate and give us a vote - this is the easiest way for you to give back to RapidMiner.

Please support us by voting for RapidMiner here:
 
http://www.kdnuggets.com/2016/05/poll-analytics-data-mining-data-science-machine-learning-software-u...

Things are incredibly simple and only take 20 seconds of your time:


  • Visit http://www.kdnuggets.com/2016/05/poll-analytics-data-mining-data-science-machine-learning-software-used.html

  • Select RapidMiner in the list at the bottom of the page

  • Confirm your selection via email



Don't worry: KDNuggets will not use your mail address for any other purpose than for this confirmation.

Please vote for RapidMiner in the annual poll of KDNuggets and help us to get more widely known among analysts and researchers worldwide.  Help us to spread the word!

Cheers,
Ingo

How to load processes in XML from the forum into RapidMiner: Read this!
2 REPLIES
Contributor I MCs
Contributor I

Re: Please vote for RapidMiner at KDNuggets 2016

Looking at current results it is nice to see RMs great performance 

Fingers crossed...

 

Predictive Marketing Analyst @ Data n Analytics Predictive Marketing Team, Europe
RM Staff
RM Staff
Solution

Re: Please vote for RapidMiner at KDNuggets 2016

Hi,

 

Just wanted to let you know that the results from KDNuggets are in.  RapidMiner was voted the most popular general platform for machine learning / data science with about 33% of all analysts using it.  This is an awesome result!

 

More can be found at http://www.kdnuggets.com/2016/06/r-python-top-analytics-data-mining-data-science-software.html

 

Many thanks to all who supported us in this poll - you are the best!

 

Cheers,

Ingo


How to load processes in XML from the forum into RapidMiner: Read this!
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