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Watch Recording / View Slides - Coming after the live event
Guest Speakers and subjects:
- Jeremy Meier, Undergraduate Student Clemson University
Evaluation of time-series prediction methods using Stored-value Card Totals
- Roger Dev, Sr Architect, LexisNexis Risk Solutions
TextVectors - Machine Learning for Textual Data
Text Vectorization allows for the mathematical treatment of textual information. Words, phrases, sentences, and paragraphs can be organized as points in high-dimensional space such that closeness in space implies closeness of meaning. HPCC Systems' new TextVectors module supports vectorization for words, phrases, or sentences in a parallelized, high-performance, and user-friendly package.
Roger is a Senior Architect responsible for the HPCC Systems Machine Learning Library. He has been at HPCC Systems for nearly three years. He was previously at CA Technologies. Roger has been involved in the implementation and utilization of machine learning and AI techniques for many years, and has over 20 patents in diverse areas of software technology.
Allan Wrobel, Consulting Software Engineer, HPCC Systems, LexisNexis Risk Solutions
ECL Tips and Tricks: Leveraging the power of HPCC Systems. Using AGGREGATE.
The ECL built-in function AGGREGATE has been seen by many in the community as ‘complex’ and as such has been underused. However in using AGGREGATE you can be sure you’re playing to the strengths of HPCC System.