Hello I'm
Pranjal Parmar
Frontend Developer
A quick learner and innovative problem-solver. I excel in projects ranging from Web Development, MERN Stack and Data Analysis, showcasing adaptability and collaboration. Passionate about impactful solutions, that thrive on challenges and continuous growth.
About Me
Frontend Developer!
An agile and innovative problem-solver, I excel in Web Development, MERN Stack technologies, and Data Analysis, consistently delivering impactful solutions. With a proven ability to adapt and collaborate seamlessly, I thrive in dynamic environments that challenge me to push boundaries and drive continuous growth. Passion lies in reading books, playing cricket, dancing down the town. Blend of having leadership qualities and working as team member too. Never forget to serve for country as well.
View MoreResume
Experience
Skills
Education
Dec 2023 - Feb 2024
Data Analytics
YBI Foundation
Servo Prediction - The model evaluation metrics provide insights into the performance of the linear regression model in predicting the rise time of the servo system. The scatter plot visually represents the agreement between the actual and predicted values.
Dec 2023 - Jan 2024
MERN Stack Developer
KJSIT
Doctor’s Appointment System - Developed a responsive and user-friendly web application for scheduling doctor appointments using React framework. Also patients can visibily able to see that Doctor is available or not. Register and Login functionalities available.
May 2023 - July 2024
MERN Stack Developer
KJSIT
Internship Portal - Implemented personalized user accounts allowing individuals to easily update and track their internship status, uploading certificates and fostering a user-friendly experience. Teachers can update internships availability as well.
Dec 2022 - July 2023
Web Development
KJSIT
College Siksha - Designed a website using HTML and CSS that shows courses and colleges available in India and abroad with register and login functionalities. Implemented a dynamic backend using PHP to handle user registration, login, and other interactive functionalities.
HTML5
CSS3
JAVASCRIPT
JAVA
PYTHON
REACT.JS
TAILWIND CSS
MYSQL
MONGODB
SQLITE
PHP
FIGMA
GIT/GITHUB
DJANGO
STREAMLIT
FLASK
2021-2025
CGPA - 9.06
K. J. SOMAIYA INSTITUTE OF TECHNOLOGY
B.TECH IN INFORMATION TECHNOLOGY
2019-2021
CGPA - 10
K. J. SOMAIYA COLLEGE OF SCIENCE AND COMMERCE
HIGHER SECONDARY SCHOOL CERTIFICATE
2007-2019
CGPA - 9.28
ST. MARY'S MULTIPURPOSE HIGH SCHOOL
SECONDARY SCHOOL CERTIFICATE
Projects
My Projects
Steel Manufacturing Defects
The Steel Manufacturing Defects project leverages deep learning models like ResNet50, CNN, and ResUNet to analyze 13,000 images for defect detection. It aims to enhance accurately identifying defective and non-defective steel products.
DJANGO, STREAMLIT, RESNET50, CNN, RESUNET, IMAGE PROCESSING, SQLITE
Doctor's Appointment System
Developed a responsive and user-friendly web application for scheduling doctor appointments using React framework. Also patients can visibily able to see that Doctor is available or not. Register and Login functionalities available.
MERN, CNN, TAILWIND CSS
Internship Portal
Implemented personalized user accounts allowing individuals to easily update and track their internship status, uploading certificates and fostering a user-friendly experience. Teachers can update internships availability as well.
MERN, TAILWIND CSS
Solar Panel Cleaning and Monitoring System
Designed and implemented a solar panel cleaning and monitoring system with a customizable interface to optimize cleaning schedules and track performance metrics by monitoring pre- and post-cleaning readings of solar panels.
IOT, HTML, CSS, JAVASCRIPT
College Siksha
Designed a website using HTML and CSS that shows courses and colleges available in India and abroad with register and login functionalities. Implemented a dynamic backend using PHP to handle user registration, login, and other interactive functionalities.
HTML, CSS, PHP
Brain Tumor Detection System
Project presents a web-based Brain Tumor Detection System leveraging a Convolutional Neural Network model. The system allows users to upload MRI scan images and personal details via a web interface.
MERN, CNN, IMAGE PROCESSING, TAILWIND CSS
Servo Prediction
The model evaluation metrics provide insights into the performance of the linear regression model in predicting the rise time of the servo system. The scatter plot visually represents the agreement between the actual and predicted values.
LINEAR REGRESSION, PYTHON, MATPLOTLIB, SEABORN