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Guest Speakers and subjects:
David de Hilster is a Consulting Software Engineer who has a B.S. degree in Mathematics and a M.A. in Linguistics from The Ohio State University. His background is in natural language processing and is one of the co-authors of the computer language NLP++including its IDE VisualText, and he has been a LexisNexis employee since December of 2015. His top responsibility is the ECL IDE which he has been contributing to since 2016.
Bob Foreman, Senior Jeremy Meier and David Noh, Undergraduate Student Students Clemson University
Evaluation of time-series prediction methods using Stored-value Card Totals
David DeHilster - Consulting Software Engineer, HPCC Systems, LexisNexis Risk Solutions
New ECL IDE features in HPCC Systems 7.0
The ECL IDE is an integrated development environment for ECL programmers to create, edit, and execute ECL code within the HPCC Systems platform. The latest 7.0 version includes new features and enhancements such as a more comprehensive autocomplete, tooltips and F12 capabilities. In this talk, David will discuss how users can leverage these features and more.
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An Investigation into Time Series AnalysisOver the past several months, our team has worked closely with a dataset having roughly 16,000 total observations, recording both the date and balance in financial data. Focusing on individual accounts with a size of around 400 observations, our first goal was to compare statistical metrics and techniques used commonly in time series analysis on the given data sets. We dove deep into two major industry standard methods for understanding and predicting on a dataset. Using insights learned from these observations, we hope to better predict future balances in the dataset, as well as find any anomalies or misbehavior in the data in order to provide business value.
Jeremy is a senior undergraduate student, majoring in Computer Science at Clemson University. He is originally from Greenville, South Carolina, and he is conducting research with Dr. Apon’s group with a focus on time series analysis. In the past, he has worked with HPCC Systems in the development of text analysis libraries. His other interests include bioengineering and animation.
David is a senior undergraduate student, majoring in Computer Science at Clemson University. He is working on research with a focus on machine learning algorithms and time series analysis. His interests include machine learning algorithms and high performance computing.
- Roger Dev, Sr Architect, LexisNexis Risk Solutions Group - Watch Recording
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 Group - Watch Recording
ECL Tips and Tricks: TBC Bob Foreman has worked with the HPCC Systems technology platform and the ECL programming language for over 5 years, and has been a technical trainer for over 25 years. He is the developer and designer of the HPCC Systems Online Training Courses, and is the Senior Instructor for all classroom and Webex/Lync based trainingLeveraging 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.