If you are into machine learning and racing cars, this event is for you! Join us online, November 26th, when Trifork will give you an intro to the extremely cool Donkey Cars – a small-scale remote-controlled car mounted with a RaspberryPi, a sensor and a camera.
You will be guided through how to set up the Donkey Car, how to install pre-recorded data, how to train and tweak machine learning models and deploy them on the car.
When you have attended this event, you will be fully ready to enter the Donkey Car Race event where we will meet and compete – hopefully next semester. In the meantime, you can practice your racing techniques and train your algorithms in ORBIT Lab or in Trifork.
About Donkey Cars
Donkey is an open-source DIY platform for small scale cars with a high-level self-driving library written in Python. A Donkey Car consists of standalone, independently configurable components that can be combined to make a car. Read more about Donkey Cars.
16.30: Welcome, by ORBIT Lab and Trifork
16.35: Intro to Donkey Cars
16.50: Demo setup + initial training
17.10: Machine Learning, mainly image recognition
17.25: Self-driving car demo (deploying the model on the Donkey Car)
17.40: Final discussion: Potential issues and possibilities for optimization
18.00: Thank you for today
* The times in the program are estimates
About the speakers
Iulia Adriana Popa
Iulia is a software pilot at Trifork. She is passionate about coding and learning new technologies. When she is not coding, she can be found stuck with her nose in a book, playing WoW or on a yoga mat
Simon is an ICT engineer with a degree from Aarhus University, as well as a former ORBIT Lab mission specialist, who now works as a Software Pilot at Trifork. As a part of the ML team at Trifork, he specializes in applied natural-language understanding within the service industry.
David finished his Master’s degree in Computer Science from Aarhus University last year, where he specialized in ML, NLP and functional programming. He currently works as a Software Pilot and backend developer at Trifork. In his free time, he enjoys running, League of Legends and working on spare time coding projects.
Who can participate
This event is free and open for students, tech startups and other people with an interest in the topic. You don’t have to be an expert in machine learning, as we will deal with entry-level machine learning.
This event will be in English.
Online – Participants will receive a link to Microsoft Teams on the day of the event.
By signing up for this event, you agree to receive email updates from ORBIT Lab, e.g. changes in connection with this event. You can manage your preferences and unsubscribe at any time, however, please remain “subscribed” until after the event, as we will communicate potential changes to subscribers only. Please note, the signup form may not work in Firefox for Windows. Please use another browser.
Technical questions may be addressed to Trifork Software Engineer, Simon Kæseler on email@example.com.
General questions may be addressed to Litte Dalsgaard, ORBIT Lab Community Manager: firstname.lastname@example.org / 93 52 14 47.