Passionate about data science with a strong interest in exploring its potential. Completed machine learning and gained foundational knowledge of neural networks and deep learning. Skilled in data analysis, model building, and problem-solving. Enthusiastic about applying my skills to real-world projects, with a continuous drive to expand my expertise and contribute to impactful solutions.
+91 8469409852
PR:95.31
CGPA: 9.75
• During my internship, we developed both a Hotel Management website and an e-commerce platform using the MERN stack These projects involved creating user-friendly interfaces for booking rooms, managing reservations, handling customer data, and facilitating online shopping.
• Introducing our cutting-edge weather app crafted with HTML, CSS, and JavaScript, delivering live updates on-the-go. With a minimalist design and lightning-fast performance, stay ahead of the weather curve effortlessly. Just input your location and receive real-time forecasts, covering everything from temperature trends to wind speeds.
• Built personalized portfolio website with React.js, showcasing skills and projects. Implemented responsive design, React components, and interactive features for optimal user experience.
FarmSmart uses machine learning to recommend the best crops for farmers based on soil type, weather conditions, and environmental factors. By leveraging models like Random Forest, SVM, and XGBoost, it provides accurate, data-driven crop suggestions. The user-friendly Streamlit interface allows farmers to easily input data and receive actionable recommendations for better crop selection and improved yield.
This project uses machine learning to predict home prices in Bangalore based on factors such as location, area, and amenities. By applying data preprocessing and models like linear regression, it provides accurate price predictions. The system helps potential buyers and real estate professionals make informed decisions by offering data-driven insights into market trends.
This project uses Support Vector Classifier (SVC) to classify images of sports celebrities. It applies feature extraction techniques to process the images, enabling accurate categorization into different celebrity classes. The system demonstrates the power of machine learning in image recognition tasks, ensuring high accuracy and efficiency in identifying sports figures.
Designed compelling data visualizations using Power BI to illustrate trends and patterns in crime and road accidents across India. Leveraged dynamic dashboards to showcase comprehensive insights, empowering stakeholders with actionable information for informed decision-making and strategic interventions.
Real-TimeChatApp is a Node.js-based application designed to facilitate instant messaging and real-time communication between users. Built upon the principles of WebSocket technology, this chat app provides a seamless and responsive chatting experience, allowing users to exchange messages in real-time without the need to refresh the page.