Deep Learning Models for Automated Cervical Cancer Detection
Summary
Led the development of a deep learning system for automated cervical cancer detection, utilizing CNN in MATLAB R2018 to improve diagnostic accuracy and efficiency.
Highly motivated B.Tech graduate in Electronics and Communication, leveraging a strong foundation in Java, MySQL, and Web Development to build responsive applications and apply deep learning for real-world problem-solving. Eager to contribute technical expertise and a proactive learning approach to dynamic IT teams, driving innovation and continuous skill development.
Python Programming Intern
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Summary
Contributed to foundational Python projects and automation scripts, gaining practical experience in problem-solving and clean code practices.
Highlights
Developed foundational Python projects and automation scripts, enhancing operational efficiency and task automation.
Applied Python for practical problem-solving scenarios, contributing to project deliverables and skill development.
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Bachelor of Technology
Electronics and Communications
Grade: 8.82/10.0
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Intermediate
Intermediate
Grade: 9.0/10.0
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SSC
Secondary School Certificate
Grade: 9.7/10.0
Summary
Led the development of a deep learning system for automated cervical cancer detection, utilizing CNN in MATLAB R2018 to improve diagnostic accuracy and efficiency.
Java, Python, HTML, CSS.
MySQL.
Git, GitHub, VS Code, MS Word, MS Excel, Cursor AI.
Problem-Solving, Adaptability, Time Management, Collaboration, Communication.
Issued By
Google Workspace
Issued By
QSpiders
Issued By
Vault Of Codes
Native
Fluent