I am an enthusiastic and detail-oriented IT graduate with a foundation in programming, web development, and database management. I enjoy building efficient, scalable, and user-friendly applications and thrive in collaborative, agile environments. I am a quick learner who stays curious about the latest technologies and loves turning ideas into tangible solutions.
During my studies and internship, I collaborated on NLP projects at IIT Delhi, built an agriculture information web portal, and developed an IoT-based water quality monitoring system. I am seeking a graduate-level Front-End Developer role where I can contribute to innovative projects and grow within a dynamic team.
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Gathered a dataset containing relevant features for PCOS prediction such as hormonal levels, symptoms and medical history. Acquire a diverse set of ultrasound images from patients diagnosed with and without PCOS. Performed data preprocessing. Then split the dataset into training and testing to train the model and evaluated its performance. After that used the pre-trained ResNet-50 and VGG16 architecture for ultrasound image classification. Then integrated with the XAI techniques like LIME , GradCAM and evaluated the model performance using standard metrics such as accuracy.
Created the responsive web application that shows the information and connect with farmers directly.
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