The proposal application period for the 2021 HPCC Systems intern Program is now open.
The deadline date for proposal applications is Friday 19th March 2021.
Discuss your ideas with the project mentor and send your final proposal to Lorraine Chapman.
This project was completed during the 2020 HPCC Systems Intern Program by Jack Fields, American Heritage School of Boca/Delray, USA.
Find out about the HPCC Systems Summer Internship Program.
Resources Available to Learn More about this completed project:
Process Robotics data with HPCC Systems Platform. Previous intern project by American Heritage High School (AH) student Aramis developed ROS package to collect data from various sensors and spray to HPCC Systems Thor. Aramis also created some ECL code to graph some data with HPCC Systems libraries. In this project we try to go to a further step to process some data. One of the possible area is images collected from the Robotics developed by AH recently. The project will try to train a model with HPCC Systems Machine Learning (ML) General Neural Network (GNN) which support TensorFlow and apply it new data.
If you are interested in this project, please contact the mentors using the details below.
Completion of this project involves:
- Producing design documentation
- Develop GNN ECL code to train a model
- Checked in code
Data processing with HPCC Systems involves:
- Learning HPCC Systems architecture
- Learning ECL
- Learning HPCC Systems ML GNN
- HPCC Systems GNN (TensorFlow)
- Docker Image
- Hyper-V (VHD)
- AWS AMI
Processing image data with HPCC Systems GNN involves:
- Collecting images
- Pre-processing the images. For example should we need down size the image?
- Spraying the image data to thor
- Use GNN to train the model. There are lots of works needed here. Mainly find suitable hyper-parameters
- Saving the model
- Using the model for the new image data.
By the mid term review we would expect you to have:
- Sprayed image data to Thor
- Written initial ECL code
- Trained a model with HPCC Systems GNN with some initial result
David De Hilster
Backup Mentor: Xiaoming Wang
End of project