About

Welcome To My Portfolio.

        I am aspiring Full-Stack Developer skilled in Java, Python, and JavaScript, with expertise in building scalable applications using Spring Boot, React, and MySQL. Passionate about optimizing performance and leveraging machine learning to drive innovative solutions.

Skills


  • Programming Languages:
    • Python
    • Java

  • Frameworks/Libraries:
    • Spring Boot
    • Hibernate
    • React

  • Databases:
    • MySQL
    • Oracle

  • Version Control:
    • Git
    • GitHub

  • Developer Tools:
    • Visual Studio
    • Jupyter Notebook
    • Co_lab
    • Intellij IDEA

  • Operating System:
    • Window
    • Linux
    • MacOS

  • Certifications:
    • Coursera
    • Udemy
    • NPTEL course

  • Communication:

  • Team Work:

Education

Madanapalle Institute of Technology and Science

2019 – 2023

B. Tech in Computer Science & Engineering

CGPA : 8.21/10.00

Deep Boarding High School

2017 – 2019

Science

Percentage : 79.5/100

Ramapur Revival English Boarding School

2017

Percentage : 79.5/100

Project

Social-Media-Platform

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Details

Platform that empowers users to connect, share content, and engage with others, aligning with a mission to empower every person and organization.

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TuneHub

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Details

Designed and implemented a TuneHub website using HTML, CSS, and JavaScript with React, offering a user-friendly interface and engaging user experience. Applied fundamental web development skills to create an interactive platform suitable for all user and provide the feature to listen music similar to spotify.

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QuizWeb

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Details

Designed and implemented a quiz website using HTML, CSS, and JavaScript with React, offering a user-friendly interface and engaging user experience. Applied fundamental web development skills to create an interactive platform suitable for beginners, fostering a seamless learning environment.

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Mental Health Prediction ML

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Details

Demonstrated proficiency in using varied machine learning algorithms to predict whether a person needs mental health treatment based on a survey dataset. Conducted data exploration, visualization, preprocessing, encoding, model building, and evaluation using logistic regression, KNN, decision tree, random forest, gradient boosting, AdaBoost, and XGBoost. Achieved high accuracy, recall, and ROC curve metrics.

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