Ravi Bandapu

Project

Grocery Store Management System

• Designed and developed a full-stack application to manage grocery store inventory and customer orders efficiently.
• Implemented front-end using HTML and CSS, ensuring a clean and intuitive user interface.
• Built a robust back-end with Python and FastAPI to handle product stock management and customer order processing.
• Integrated MySQL for persistent data storage of inventory, users, and orders.
• Enabled features for adding/removing stock items, viewing product availability, and placing customer orders in real-time.

Potato Disease Classification using Convolutional Neural Networks

• Developed a deep learning model to accurately classify potato leaf diseases using image data.
• Utilized Convolutional Neural Networks (CNN) for feature extraction and classification of disease types.
• Preprocessed image datasets with resizing, normalization, and data augmentation techniques to enhance model performance.
• Implemented the model using Python with TensorFlow and Keras frameworks.
• Achieved high accuracy in classifying healthy and diseased leaves, supporting early detection and crop protection.

File Compression and Decompression using Huffman Coding in Java

• Implemented an efficient file compression and decompression system using the Huffman Coding algorithm.
• Developed the entire project in Java, focusing on minimizing file size without data loss.
• Designed custom logic to encode characters based on frequency and generate optimal binary trees.
• Enabled both compression and decompression functionalities with accurate reconstruction of original data.
• Improved storage efficiency, making it suitable for handling large text files and reducing disk space usage.