PACE Data Mining Boot Camp 2 (April 29-30, 2015)
 
PACE Data Mining Boot Camp 2

Wednesday 04/29/15 - Thursday 04/30/2015
San Diego Supercomputer Center (SDSC), UC San Diego
10100 Hopkins Drive
La Jolla , California, 92093

 

About the Predictive Analytics Center of Excellence (PACE) Boot Camp 2
While modern databases can contain massive volumes of data, researchers are confronted with a virtual obstacle course in order to extract meaningful predictive information from within these records. During the two-day PACE Data Mining Boot Camp participants will receive the basic training to learn effective predictive analytic strategies associated with the growing discipline of data mining, a process that uses a variety of data analysis tools to discover patterns and relationships in data that may contribute to valid predictions. Predicting future trends and behaviors allows for proactive, knowledge-driven decisions. 

The PACE Boot Camp 2 is designed to provide individuals in business enterprises and scientific communities with improved tactics critical to design, build, verify, and test advanced predictive data models. Data mining—the art and science of learning from data—covers a number of different procedures. This hands-on course emphasizes advanced learning techniques including Artificial Neural Networks (ANNs), Support Vector Machines (SVM), Text Mining, Collaborative Filtering, Bayesian Networks and Temporal Data Mining. During the hands-on sessions PACE instructors will help participants hone their new skills to conquer technical obstacles to achieve their objectives. Boot Camp 2 participants will have access to a comprehensive set of data mining tools available on SDSC’s Gordon, one of the world’s most powerful supercomputers with 300 Terabytes of flash memory. Moreover, with access to this computing resource, participants will be able to sharpen their skills, apply data mining algorithms to real data, and interpret the results. 

Attendees will leave Boot Camp 2 with an arsenal of ideas and on a steady path to becoming a data scientist.

For further details on PACE, please visit our website: http://pace.sdsc.edu/