Registered user since Sun 26 Jun 2022
I’m a machine learning enthusiast working on applications such as Software Engineering and Document Analysis and Recognition.
Hey, I know you can come up with some fascinating ML models for any application that works wonderfully on the test data. How can you validate that, your model works more effectively than human, in reality? Probability + Empirical analysis is maybe the solution for this type of research problem. Yes, this is my research interest currently.
I’m currently working on validating the real-world feasibility of the DPMs in the real-world testing environments. In addition to that, I’m also working towards addressing reliability challenges that are imposed by the defect prediction models. As specified above, my focus is also on providing the practical feasibility of the well-trained handwritten character recognition models. I’m an Assistant Professor of Computer Science and Engineering at National Institute of Technology Calicut (NITC), Kerala, India. I completed my Ph.D. in the department of Computer Science and Engineering, National Institute of Technology, Warangal (NITW), India. Prior to joining NITW, I’ve completed my masters from the University of Hyderabad, India.
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