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| Date of the event | October 5th-8th 2017 |
| Location | Marietta Campus, J/Atrium Building |
| Cost | Free |
| Eligibility | This event is open to all KSU CCSE students (ACS, BASIT, IT, CS, SWE, and CGDD) who have passed their first few programming courses. Graduate students who have exempted all transitional courses or have passed at least three 5000 transition courses are also eligible. |
| Registration | More information about the event |
| HPCC Systems Hackathon Team | Machine Learning for Big Data Analytics on HPCC Systems Are you interested in how analytics can identify trends which help businesses from a wide range of markets improve their decision making? Join our team and learn how to use the open source HPCC Systems platform and ECL-ML machine learning libraries, to build predictive models in the fields of insurance, health care, finance, security and other vertical markets. |
| Challenge | Simulated Vehicle Traffic Monitoring Driver behavior can encompass an individual’s driving behavior and external factors such as the drive path, volume of traffic, traffic encountered, number of trips, where the streets are and the low/peak activity time and much more. We are providing some simulated data and would like you to establish whether this data reflects the patterns of driver behavior that we would expect to see in the real world. Meaningful data mining requires in the first instance knowledge about the shape of the data. Once this has been established, it is then possible to identify features which allow you to infer certain conclusions from the data. While we will provide some instructions about the sorts of conclusions we would expect you to discover, the main purpose of the challenge is for you to examine the data for yourself, extrapolate from that data and impress us with your own innovative thought processes and conclusions. The project goal will be achieved using the HPCC Systems platform by importing, translating and aggregating the data points in conjunction with utilizing the HPCC Systems Machine Learning Library, which provides the tools you need to build learning models from the collected data points. Although we will be looking at your final code and results, we are particularly interested in your methodology and whether your conjectures prove to be true or false. The goal will be around building models to address the challenge of the coming traffic revolution due to the introduction of autonomous vehicles. |
| Data Source | http://kolntrace.project.citi-lab.fr |
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| Mentors available during the Hackathon | The following mentors will be on site for the duration of the event: Dan Camper, Arjuna Chala and Richard Taylor. The following mentors will be available to give assistance remotely: John Holt and Roger Dev.More information about our mentors and how to contact them |
| Slack Channel | https://ksuccsehackathon.slack.com/ |
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