1 min readfrom Machine Learning

Built a Hybrid NAS tool for RNN architectures (HyNAS-R) – Looking for feedback for my final year evaluation [R]

Hi everyone,

I'm currently in the evaluation phase of my Final Year Project and am looking for feedback on the system I've built. It's called HyNAS-R, a Neural Architecture Search tool designed to automatically find the best RNN architectures for NLP tasks by combining a zero-cost proxy with metaheuristic optimization.

I have recorded a video explaining the core algorithm and the technology stack behind the system, specifically how it uses an Improved Grey Wolf Optimizer and a Hidden Covariance proxy to search through thousands of architectures without expensive training runs.

Video Explanation: https://youtu.be/mh5kOF84vHY

If anyone is willing to watch the breakdown and share their thoughts, I would greatly appreciate it. Your insights will be directly used for my final university evaluation. Live demo link is inside the form for anyone interested.

Feedback Form: https://forms.gle/keLrigwSXBb74od7A

Thank you in advance for your time and feedback!

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