SRM University bagged them the 1 st place on Angelhack Global Hackathon 2018

By- INN/Chennai, @Infodeaofficial 

A team of students from SRM University, Kattankulathur bagged the lst prize at Angelhack hackathon. It was conducted as a part of Angelhack Global Hackathon series 2018 at the Microsoft campus in Hyderabad. The theme of “Seamless Technology” was set with the intention of giving developers the freedom to use any technology without restrictions, to solve pressing problems concerning them and developers across the world.

Solutions like these would enable quicker prototyping and deployment, increasing the already exponential rate of productivity of the technology industry. Over 200 students, experienced professionals and entrepreneurs competed for this rare opportunity. After number of reviews and 2 rounds of extensive pitching sessions, the results were finally declared at the end of the 30 hrs. long event. The Judging panel comprised of professionals from Microsoft, Amazon and major start-ups.

Two students, Ankur Agarwal and Krishna Maneesha Dendukuri from Next Tech Lab of the University, were a part of this winning team. The opportunity of attending the Global HACKcelerator Program 2018 connected the students with thought-leaders and experienced entrepreneurs to help themselves in becoming more versatile while refining their ideas to build their hackathon winning prototype into a full-fledged start-up.

The team created an Artificial Intelligence based application which helps resolve bottlenecks for machine learning practitioners. Selecting the best algorithm to be applied on a given data set in order to achieve the highest accuracy rates was the problem. This required intensive data analysis and a lot of trial and error cycles of applying the models while consuming a lot of time and processing power for training.

This tedious process makes developers to treat the machine learning more likely alchemy than an exact science. These students built a solution which can predict the efficiency of 10 different algorithms without even running them, for a dataset given by the user and therefore, suggested the best one to be applied by saving the valuable resources like training time and GPU power that bagged the team the 1st place.

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