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Mahesh Ganapati Hegde

Software Developer
Student / Aspiring Software Developer

Information Science Engineering student skilled in Java, Python, and Data Structures & Algorithms

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Bengaluru, India

Headline

Aspiring Software Developer passionate about Java, Spring Boot and problem solving

About

Information Science Engineering student skilled in Java, Python, and Data Structures & Algorithms, with working knowledge of JavaScript. Built a web-based task management application, a Java console banking system, and a document classification model using Naive Bayes, applying object-oriented programming, exception handling, and machine learning fundamentals. Strong problem-solving ability and quick to learn new tools and technologies.

Education

Bachelor of Engineering

Acharya Institute of Technology, Bengaluru

Information Science & Engineering · 2023 – 2027 · CGPA: 7.39

12th (State Board)

MES PU College, Sirsi, Karnataka

Computer Science · 2021 – 2023 · Percentage: 88.5%

Projects

Ledger - Task Management Web App

Built a task manager with add, complete, and delete functionality, along with priority tagging for each task. Implemented persistent storage using the browser's localStorage API so tasks remain saved across sessions. Used event delegation for efficient DOM event handling instead of attaching listeners to individual elements.

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Simple Banking System

Developed a console-based banking application supporting account creation, deposits, withdrawals, and balance inquiries. Designed custom exception handling to prevent overdraft withdrawals and ensure data integrity. Used ArrayList to manage multiple customer accounts and maintain transaction history.

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Document Classification using Naive Bayes

Built a text document classifier using Multinomial Naive Bayes on the 20 Newsgroups dataset (2,323 training / 1,546 test documents across 4 categories). Applied TF-IDF vectorization to convert raw text into weighted numeric features, achieving 89.4% test accuracy. Evaluated model performance using precision, recall, and F1-score, and validated predictions on unseen text input.

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