Aditya Vijapurapu

Analyzed 119,390 hotel booking records to identify booking trends and cancellation reasons. Performed extensive data preparation, including outlier treatment and feature encoding. Developed machine learning models (Logistic Regression, Decision Tree, Random Forest) to predict cancellations, enabling personalized guest services and improved customer satisfaction.

Analyzed 783,667 customer purchase records to uncover purchasing patterns across demographics. Preprocessed data, including missing value handling and feature engineering. Built and evaluated machine learning models (Linear Regression, Decision Tree, Random Forest, XGBoost) to predict purchase amounts, driving targeted marketing and personalized promotions.

Optimized app performance by analyzing IPL game data using MySQL for efficient data storage and manipulation. Examined bidder, match, player, and team statistics to enhance functionality. Leveraged Tableau for data visualization, uncovering patterns and insights to improve user engagement and experience.

Contributed to developing a web application for managing ship berthing processes using HTML, CSS, and PHP. Gained experience in building and deploying web-based solutions for government operations, focusing on streamlining the ship berthing process through an intuitive user interface and backend functionality.

Developed hands-on skills in AWS services like EC2, S3, and Lambda, focusing on cloud deployment, resource optimization, and security. Gained experience in managing applications, automating tasks, and enhancing performance within the AWS environment.