Watch Recording / View Slides - Coming after the live event
Guest Speakers and subjects:
- Jeremy Meier and David Noh, Undergraduate Students Clemson University
An Investigation into Time Series Analysis
Over 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
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.