|By Marketwired .||
|December 7, 2012 02:11 PM EST||
LAKE TAHOE, CA -- (Marketwire) -- 12/07/12 -- At the annual NIPS Conference for data scientists, Skytree, Inc., an advanced analytics and machine learning company, today launched a contest for companies looking to jumpstart their advanced analytics and accelerate their big data initiatives. The winning company receives a one-year license for Skytree Server valued at $100,000, which includes consulting services and data modeling. Five runners-up will receive free machine learning consulting from a machine learning expert. Entries will be judged based on the universality, emerging data science, and clarity of the big data challenge posed. To be entered in the contest, companies may submit their "Big Data Challenge" to Skytree between December 6, 2012 and January 11, 2013 on the Skytree website.
Before presenting his technical talk at NIPS, Skytree CTO Dr. Alexander Gray announced the contest and Skytree's reasoning for putting on the challenge. "We believe machine learning has come of age just in time to meet the growing need for advanced analytics on massive datasets in business, in science and even in government," said Gray. "The winner of our challenge will get the benefit of a state-of-the art advanced analytics solution, which is exactly what many organizations need right now."
For additional details, and to participate in the contest, visit the Skytree website.
Skytree Server was developed to run machine learning algorithms on big data across 100s or 1000s of CPUs, solving advanced analytics challenges created by exploding datasets across many domains. With Skytree Server, companies can keep up with the deluge of data that is increasing in volume, velocity, and variety. With Skytree Server, the company provides an array of advanced analytics and machine learning solutions, including Skytree's newest PowerPack Plugins and Jump Start Packages for companies at any stage, and data sets of any size.
Jump Start packages include the Skytree Server platform and added capabilities allowing customers to:
- Explore. Demonstrate and explore the feasibility of using machine learning to achieve a specified business goal and offer a world-class team which works with organizations to get them up and running with machine learning;
- Prove. Demonstrate and explore the feasibility of using fast/scalable machine learning to improve performance toward a specified business goal by working with an organization's data scientists to help increase big-data machine learning capabilities;
- "Go Crazy". Unleash the power of using fast/scalable machine learning to achieve unprecedented results by working with an organization to explore what is possible with the best statistical and computational information to create or improve a product, service, or capability with game-changing effects.
Skytree's Machine Learning platform gives organizations the power to discover deep analytic insights, predict future trends, make recommendations and reveal untapped markets and customers. Predictive Analytics and Machine Learning are quickly becoming must-have technologies in the age of Big Data, and Skytree provides the Enterprise-grade foundation. Skytree's flagship product -- Skytree Server -- is the only general-purpose scalable Machine Learning system on the market, built for the highest accuracy at unprecedented speed and scale. For more information visit www.skytree.net and follow Skytree on Twitter @SkytreeHQ.
New Venture Communications
Software AG helps organizations transform into Digital Enterprises, so they can differentiate from competitors and better engage customers, partners and employees. Using the Software AG Suite, companies can close the gap between business and IT to create digital systems of differentiation that drive front-line agility. We offer four on-ramps to the Digital Enterprise: alignment through collaborative process analysis; transformation through portfolio management; agility through process automation and integration; and visibility through intelligent business operations and big data.
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