It's that time of year again! The HPCC Systems Intern Program is well underway. In 2021, we have welcomed 12 students on to the program to complete a range of projects contributing to our open source platform and machine learning library. Now that the students are well into their project tasks, now is a good time to share progress made so far.

It is well known in the Machine Learning community that data preparation is the most time-consuming phase of a Machine Learning project. To make that phase smoother on the HPCC Systems platform, Vannel Zeufack has provided a machine learning preprocessing bundle. This work was completed as an intern project in 2020, when Vannel joined the program for the second year running.

One of the biggest concerns that we have in education is the safety of our school campuses. To address this problem, the American Heritage School robotics team developed an autonomous, mobile robot that gathers and provides vital information to school security personnel, and, if necessary, first responders. This blog details the facial recognition training project completed by HPCC Systems summer intern, Jack Fields, a 12th grade high school student at American Heritage School in Delray, Florida.

HPCC Systems is going cloud native, and the cloud development team has been active with projects related to the new” HPCC Systems cloud native platform.” A number of these projects were implemented by summer interns. This blog details the cloud platform projects completed by Jefferson “Jeff” Mao, a 12 grade high school student at Lambert High School in Suwanee, Georgia.

Time series forecasting is an important statistical tool for predicting future events, needs, trends, etc., and can be applied to a variety of data sources. Jeremy Meier and David Noh, recent graduates of Clemson University’s Computer Science program, spoke at HPCC Systems Tech Talk episode 23 about the basic principles and components of time series forecasting using modern machine learning methods. This blog gives insight into their semester-long project, which focused on time series analysis and forecasting using financial datasets.