On the weekend of 26^th & 27^th June 2021, students and data science enthusiasts from all around the world took on the first ecological hackathon organised by Veolia and the Tara Ocean Foundation – with the support of the oceanography laboratory of Villefranche, Sorbonne University and Plankton Planet.

The challenge? Participants had 48 hours to come up with a machine learning model that can classify hundreds and thousands of plankton photos taken during the Tara Ocean Foundation’s current expedition around the world. Plankton are the principal producers of atmospheric oxygen and the vital first link in the oceanic food chain, thus are an essential component of life on Earth.

The hackathon places a huge emphasis on energy frugality, whereby the model proposed must be able to run under low power utilising Raspberry Pi as the hardware component. Participants have to also imagine the best way to visualise the data. Eventually, the model will be used on the Tara Schooner to work with the Planktoscope, the system developed by Plankton Planet and Stanford University to capture images of plankton in water samples.

TEAM HAWAIIANBOBTAILGREEN7!

A team from 42 Kuala Lumpur (42KL), a computer-science programming school based in Sunway City took on the challenge and went through a gruelling 48-hours, of which were mostly spent on learning the fundamentals of machine learning. Suresh Chetty, Hans Hazairi Baddrul Hezri, Gates Tan & Bunyod Shamsiddinov came from various backgrounds, and applied the same principles of 42KL’s pedagogy during the hackathon.

Together, not only did they managed to secure a seat in the Top 8 finals, but they were also the only team that had successfully developed a machine learning model with a plankton identification accuracy that is higher than that of the current model used onboard Tara Schooner.

“The challenge was immense as none of us had any prior exposure to machine learning, and I had never explored Python programming language. So, we initially just took it as a way for us to speed-learn machine learning models” said Gates Tan who was a medical science graduate prior to joining 42KL. By applying the same peer-to-peer learning pedagogy at 42KL, the team decided to learn as much as they could about machine learning prior to the start of the hackathon. “Right after we had registered for the event, we studied various machine learning videos and tutorials, and we were confident before the hackathon. But when it started, we quickly realised that everything that we had studied before was useless and we have to develop something much bigger than just a beginner model” said Bunyod Shamsiddinov who is just 19 years old and is one of the youngest cadets (students) in 42KL.

“And you also have to be absolutely sure that the model you have developed will work because it takes time to train your machine learning model. So, there was a lot of going back to the drawing board for us” he continued. But through their experience of working together, solving challenges with zero knowledge to begin with is what 42KL has prepared them for from the beginning. This, combined with their own unique skill sets, the team discovered an approach that could train their model to work with a variety of datasets. “The Piscine bootcamp at 42KL really changed the way I learn. It is a lot quicker for me to learn new stuff now and I just like how everyone at 42KL has the same spirit of learning” said Hans Hazairi, a former civil engineer who resigned from his previous role to upskill himself. This sentiment was also echoed by Suresh Chetty, a former freelance Python & Django developer, “it’s more collaborative. You bring what you know to the party, nobody needs to stand out and we collaboratively see how everything falls into place”.

After completing the hackathon in 48 hours, the team was then invited to present their model in front of a panel of judges composed of Veolia and Tara employees. While the team had the most accurate machine learning model, they lost the top spot due to the energy consumption needed to operate their model in the middle of the ocean with no internet access. “They were very transparent with us on where we did not do as well as the top placed team, but we were just surprised that we got this far.” said the team.

The team is now currently focused on improving their machine learning model in hopes that it could be applied into other verticals such as agriculture where food security is a major concern here in Malaysia. “In the future, we are hoping to apply this model and learning to be used for other types of identification such as the health of our plants and vegetables.” said the team. One future project could be a collaboration with Sunway FutureX Farms, Malaysia’s first innovative urban farm R&D hub, producing fresh, pesticide-free vegetables using sustainable and safe farming technology

About 42 Kuala Lumpur

No Teachers. No Classes. No Lecturers. No Tuition Fees.

42 Kuala Lumpur (42KL) is a tuition-free computer programming school with a peer-to-peer learning environment that does not involve teachers and lectures. We use an innovative education model that was designed to develop the skills needed to jumpstart a career as a software engineer using a project-based learning approach. We are not a traditional university, and we are not a coding bootcamp.

42KL offers an unparalleled educational opportunity to any Malaysian, regardless of socioeconomic status and educational background. The concept has received tremendous traction in cities around the world, including Silicon Valley, and we are now ready to pioneer this tech talent development game-changer here in Sunway City Kuala Lumpur.

42KL is organised by the Sunway Education Group, the Jeffrey Cheah Foundation, Sunway iLabs and MDEC, and is supported by industry partners such as Sunway Group, CIMB, DHL, Roland Berger, Carsome, Huawei, HSBC, SIDEC, Standard Chartered, FWD Insurance, Tenaga Nasional Berhad & Celcom.

Visit www.42kl.edu.my for more information. Applications are open to any individuals who are 18 years old and above. No coding/programming skills required!

For media enquiries,
please email community@42kl.edu.my