JRF/SRF Recruitment Management System
Tech Stack: React.js, Node.js, Express.js, MongoDB
A web application was built using the MERN stack to automate the recruitment process for Junior and Senior
Research Fellowships. It enables candidates to register, upload documents, and track their application
status, while providing administrators with tools to manage and evaluate applications efficiently.
GitHub Repository
Automated Cyber Defence and Cryptanalysis Toolkit
Tech Stack: Python, Scapy, Regex, Socket, Logging, Tkinter (GUI)
A Python-based cybersecurity toolkit was developed with modules for honeypot deployment, network traffic
analysis,
endpoint file monitoring, and cryptanalysis of weak ciphers. These components were integrated into a
centralized
dashboard, allowing users to control modules and view real-time logs for better usability and threat
tracking.
GitHub Repository
Product Review Sentiment Analysis Project
Tech Stack: Python, Pandas, SQL, Data Visualization
The Product Review Sentiment Analysis project utilizes natural language processing (NLP) techniques
to
determine the sentiment of a given product review. It processes textual data to classify reviews as
positive or negative
and visually represents the sentiment strength using a bar indicator. This bar dynamically adjusts to show
the extent of
positivity or negativity, providing users with a clear understanding of customer sentiment. The project
enhances
insights into customer feedback, helping businesses analyze user opinions effectively.
GitHub Repository
Brain Tumor Detection Project
Tech Stack: Python, TensorFlow, Keras, OpenCV
This project utilizes AI/ML algorithms for image recognition and classification to detect
whether an input
MRI scan
contains a brain tumor. It processes medical images using deep learning models, extracting patterns and
features to
classify scans as tumor-positive or tumor-negative with high accuracy. By leveraging computer
vision
techniques, the
system enhances early detection, aiding in faster and more reliable diagnosis for medical professionals.
GitHub Repository
Employee Salary Prediction using ML Techniques
Tech Stack: Python 3.11, scikit-learn, pandas, Streamlit, ngrok
This project was developed using Python 3.11 with libraries such as scikit-learn for machine learning,
pandas for data
handling, and joblib for saving models. It predicts the salary class (≤50K or >50K) of an individual based
on 13 input
parameters using algorithms like Gradient Boosting and Naive Bayes. A user-friendly interface was built
using Streamlit,
and the app was deployed via ngrok from Google Colab for public access.
GitHub Repository
Real Time Weather Application
Tech Stack: HTML, CSS, JavaScript, OpenWeatherMap API
The Weather Application allows users to search for a specific location and retrieve live weather
statistics.
It fetches real-time data from the OpenWeatherMap API, displaying key weather details such as
temperature,
wind speed,
and overall weather conditions. The application provides an intuitive and user-friendly interface,
ensuring
quick and
accurate weather updates for any searched location.
GitHub Repository
