MTSU Data Science and Amazon Partner to Host Machine Learning Competition
As the model racing car sped along the fictional road course on the atrium floor of the MTSU Science Building, a member of the MTSU Data Science team frequently had to pick it up and redirect it to stay on the road.
Not at all what the team had expected, but it was an issue that baffled the five teams that had spent the past two months dabbling in the increasingly important field of machine learning. It was part of a friendly self-driving model racing car competition organized by the MTSU Data Science Institute in partnership with Amazon Web Services.
“We are testing all of this together so that we can improve,” said biology professor Ryan Otter, director of the Data Science Institute at MTSU. “It’s the real world, so it’s not always pretty and perfect. … This is just the beginning.
Otter made the factual observation as he watched from the steps of the atrium, which was recently transformed into a hands-on exploration lab for the first of what Otter plans to be many “AWS DeepRacer” events. organized by the university. .
DeepRacer allows developers of all skill levels to “get their hands on machine learning via a cloud-based 3D racing simulator, a fully autonomous 1/18 scale race car driven by reinforcement learning.” Amazon Web Services describes it as “an interesting and fun way to get started” in machine learning.
MTSU’s data science program fielded two teams of students in the Nov. 13 competition, along with two teams from Central Magnet School in Murfreesboro and one team from Smyrna High School. The goal was to see which team had developed the best computer training model to help their race car navigate autonomously on the small track set up in the atrium.
Otter said members of the student team were “learning to drive in their cars” within the past two months. How? ‘Or’ What? The car is fitted with cameras which constantly take pictures of its surroundings and this information is used to develop a driving model which is then uploaded to the race car, first in a virtual environment and then for the ultimate test on the road. atrium track.
Kendra Givens, a second year student at Murfreesboro and a member of the MTSU Dream Team, was a little disappointed with the result due to the model car’s difficulties on the atrium course despite much better results in the atrium. virtual simulations leading to the November 13 Competition.
To his surprise and that of everyone, even Amazon engineers in attendance, the enormous amount of natural light inside the atrium of the Science Building on a sunny Saturday afternoon took a toll on the performance of the models, rendering difficult for one of them to make a turn on the track. . While the students created simulated runners that could complete the virtual course for 11 to 15 seconds, actual model runners took more than a minute to complete one lap – if they completed one lap at all.
A makeshift black curtain was eventually used to shield the models from all natural light, with limited success. Despite the disappointment, Givens said she would definitely attend similar events in the future – as long as things were tested in advance, she said with a smile.
“We spent a lot of time working on it. … I want to do machine learning as a career, that’s what it was, ”she added. “It was fun. The ending wasn’t fun, but working on it and seeing the model get better and better was fun.
Industry “looking for bright young talents”
Joseph Hart of Amazon Web Services, a Nashville-based senior account manager as well as a former MTSU student (’90), said the benefit of such events for Amazon is “being able to play a role in the inspiration from young minds in the data world. , analytics and data science, and what’s emerging in those areas and how it affects the business that we are in and really all businesses these days.
Like Otter, Hart said it’s important for the data science industry to involve students from an early age in this interdisciplinary field of study. Hart himself was an English literature student who landed a tech-related job as part of a college co-op program – and has been in the industry ever since.
“From a workforce perspective, when you look across the state of Tennessee, we’re looking for bright young talent who intimately understand the details involved in high performance computing, analytics, data science. , machine learning – that’s what we’re here to do, ”said Hart, who believes it’s important to engage students in data science even at the college level.
“We want to hire the best and the brightest, but we also have a responsibility to be a good corporate citizen and to improve the communities in which we live,” he said.
Central Magnet senior Calvin Guzman and Douglas Thibodeaux thanked teachers such as engineering professor Marc Guthrie for seeking such opportunities “to take engineering students to the next level.”
“I love cybersecurity and business, and AI (artificial intelligence) can be used for a lot of different things,” said Guzman, who added that his father is active on the Sports Car road racing circuit. Club of America, sparking interest in the DeepRacer Plus event.
While Thibodeaux said he was more interested in biochemistry, “I found it fun to do. It helped me learn coding because I didn’t know much about it before. And I’m not great at artificial technology and learned about it. “
For Otter, that’s the whole point.
“What matters most to us… is that you don’t have to be a computer programmer for 10 years to do this,” said Otter. “We need to lower this barrier to entry. We want more people – younger people, more diverse individuals, of all ages, backgrounds, all of that – to have access to it. “
He said that traditionally people interested in technology have been asked to “focus on computing for 10 years and if you do that you can do some really cool things.” I think this is the opposite of what we should be doing. We should show people this is what you can do that’s really awesome and then give yourself access so you can do it in a short window. “
Amazon provided access to some of its best engineers and programming platforms as part of the competition, even bringing in several of its employees to support the MTSU competition.
“It’s a low entry point, but experts can play too,” Otter said. “It’s a really great opportunity to get people involved. … It’s a real world engagement.
For more information on MTSU’s Data Science program, visit https://www.mtsu.edu/datascience/institute/index.php.