nagadevi Perabathula

I am an Electronics and Communication Engineering graduate with hands-on experience in machine learning, embedded systems and hardware design. I completed multiple academic and personal projects applying CNNs, clustering and communication protocols to solve real problems.

My machine learning work includes comparing CNN architectures on CIFAR-10, achieving 86.63% accuracy with VGG16 and building a Gradio-based real-time classification tool. I have experience with K-Means customer segmentation (identifying five segments and improving targeting accuracy) and regression-based admission prediction projects.

On the hardware side, I implemented a UART protocol in Verilog on Vivado and developed a line-follower robot using Arduino, focusing on reliable signal handling and sensor calibration. I am comfortable with tools such as Vivado, Multisim, LTSpice, and microcontroller development environments.

I hold certifications in drone innovation, machine learning training with hands-on projects, and PCB design using CAD tools. I am actively seeking a Machine Learning Internship or AI Developer Trainee role where I can contribute to impactful projects and continue learning.