KSU Event: Distributed Machine Learning with HPCC Systems
Thank you attendees for joining us! Below are the materials from the meetup.
- Download presentation
- Download VM and binaries
- R, JDBC and Pentaho integration
- Access source code and available plugins
- Machine Learning Library
- Access Demos
- View photos
LexisNexis will be speaking at a KSU event.
Wednesday, January 30, 2013 11:00am KSU Campus Kennesaw, GA
Admittance is limited to KSU faculty, students and alumni.
HPCC (High Performance Computing Cluster) Systems from LexisNexis is an open source massive parallel-processing computing platform that solves Big Data problems. Included in the platform is an extensible set of fully parallel Machine Learning and Matrix processing algorithms to assist with business intelligence; covering supervised and unsupervised learning, document and text analysis, statistics and probabilities, and general inductive inference related problems. ECL, the high level declarative data oriented programming language used with the HPCC Systems platform along with the associated Machine Learning toolkit, offer effortless linear scalability across entire clusters. A set of fully parallel linear algebra operations, written in ECL, provides extensibility, allowing for the quick implementation of new high level algorithms.
Dr. Flavio Villanustre, VP Technology Architecture and Product for LexisNexis, will present an overview of the existing capabilities and algorithms of the HPCC Systems platform and ECL language and share our latest developments in distributed machine learning and how to leverage the most appropriate algorithms to quickly extract knowledge from big data to help make critical decisions.
Open discussion to follow. Attendees will have a chance to win a Kindle Fire! Refreshments will be served. Seating is limited.