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.
- ✍ You can find my resume here :   Resume
- 📫 How to reach me:   Shyamlal9802@gmail.com
- 🌱 Currently working on Project:   Social Media Platform
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
Details
Platform that empowers users to connect, share content, and engage with others, aligning with a mission to empower every person and organization.
Click here : Learn moreTuneHub
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.
Click here : Learn moreQuizWeb
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.
Click here : Learn moreMental Health Prediction ML
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.
Click here :Learn more