Kumkumagunta Umamaheswari
Motivated and detail-oriented Computer Science graduate with a strong foundation in full-stack web development using Python, Java Script, HTML, CSS, Flask, FastAPI, SQL, and Mongo DB. Passionate about building responsive web applications, develop- ing REST APIs, and solving real-world problems through clean, efficient code.
Familiar with Git, API integration, and database management, with hands-on experience in academic projects. Eager to contribute, learn new technologies, and grow as a Full Stack Developer in a collaborative team environment.
Experience
Web Designer Intern
Sparks to Ideas
Designed and developed a responsive static website using HTML and CSS. Focused on clean UI, layout consistency, and user-friendly navigation.
Education
Rishi MS Institute of Engineering and Technology for Women(JNTUH)
B.Tech
CGPA: 7.9
Skills
PythonJavaScriptSQLHTMLCSSReact.jsFlaskFastAPINode.jsGitGitHubAPI IntegrationCommunicationTeamworkAdaptabilityStreamlitScikit-learnNLPTF-IDFOpenCVTensorFlowYOLOCOCO DatasetIoT
Projects
AI Powered Student Innovation, Career and College Guidance Hub
Built an AI-based platform with chatbot and recommendation features to guide students in career and college selection. Built using web technologies and machine learning concepts to provide personalized guidance based on student interests and academic performance. Designed a simple and user-friendly interface for easy access to guidance resources.
Farming Predictions Made Easy
Designed a Streamlit-based platform for crop and fertilizer prediction using machine learning techniques. Integrated weather, soil, and market analysis using real-time APIs to support data-driven agricultural decisions. Recommended suitable crops based on climate and soil conditions to improve farming productivity.
Fake News Detection System
Developed a machine learning model to detect fake and real news using TF-IDF and Logistic Regression. Achieved 95 percent accuracy. Evaluated performance using Confusion Matrix, Precision, Recall, F1-score.
Object Detection System
Implemented a real-time object detection system using OpenCV and deep learning models. Improved detection accuracy using the COCO dataset and live video analysis.
Internships & Certifications
Code Unnati (SAP & Edunet Foundation)
Completed hands-on training in Machine Learning, Deep Learning, and IoT. Worked on practical projects and learned industry-oriented technical skills.