Full Name
Uppala Sowmya
Which role are you applying for?
Full-Stack (Both)
Tech Stack Proficiency
Brief Overview of Experience
I have worked on multiple real-world projects during my academic and internship journey, focusing on machine learning, backend development, and full-stack applications.
One of my key projects is Intelligent Pothole Detection using Deep Learning. In this project, I developed a system that detects potholes on roads using image and video data. I used YOLOv8 (a CNN-based object detection model) to identify potholes and draw bounding boxes around them. I also performed image preprocessing using OpenCV techniques like grayscale conversion and cropping to improve model performance. The model was trained using Python with TensorFlow, NumPy, and Pandas, and I improved its accuracy through data preprocessing and augmentation techniques.
Additionally, I worked on a Credit Card Fraud Detection system, where I built machine learning models like Logistic Regression and Random Forest to classify transactions as fraudulent or genuine. I handled data preprocessing, feature scaling, and class imbalance, and deployed the model using Flask for real-time predictions.
I also developed a Travel Assistance Management System, a full-stack web application using Java, MySQL, HTML, CSS, and JavaScript. It automates booking and itinerary management while ensuring efficient database operations and responsive UI.
Alongside projects, I am currently working as an App Development Intern, where I develop backend APIs using Flask, manage PostgreSQL databases, and test APIs using Postman, gaining hands-on experience in real-world software development.
Resume Link / Upload
https://drive.google.com/file/d/17lchzs5w3kpTbE4k6YUiGwIOBirK3wmV/view?usp=drivesdk
Availability
Full Name
Uppala Sowmya
Which role are you applying for?
Full-Stack (Both)
Tech Stack Proficiency
Brief Overview of Experience
I have worked on multiple real-world projects during my academic and internship journey, focusing on machine learning, backend development, and full-stack applications.
One of my key projects is Intelligent Pothole Detection using Deep Learning. In this project, I developed a system that detects potholes on roads using image and video data. I used YOLOv8 (a CNN-based object detection model) to identify potholes and draw bounding boxes around them. I also performed image preprocessing using OpenCV techniques like grayscale conversion and cropping to improve model performance. The model was trained using Python with TensorFlow, NumPy, and Pandas, and I improved its accuracy through data preprocessing and augmentation techniques.
Additionally, I worked on a Credit Card Fraud Detection system, where I built machine learning models like Logistic Regression and Random Forest to classify transactions as fraudulent or genuine. I handled data preprocessing, feature scaling, and class imbalance, and deployed the model using Flask for real-time predictions.
I also developed a Travel Assistance Management System, a full-stack web application using Java, MySQL, HTML, CSS, and JavaScript. It automates booking and itinerary management while ensuring efficient database operations and responsive UI.
Alongside projects, I am currently working as an App Development Intern, where I develop backend APIs using Flask, manage PostgreSQL databases, and test APIs using Postman, gaining hands-on experience in real-world software development.
Resume Link / Upload
https://drive.google.com/file/d/17lchzs5w3kpTbE4k6YUiGwIOBirK3wmV/view?usp=drivesdk
Availability