Vaishnavi Vanam

• Helped with grading assignments and tests, providing constructive feedback to students based on results.
• Assisted teachers with classroom management and document coordination to maintain positive learning environment.

Project – Analysis of Ford Car Price Prediction

Analyze data using Machine Learning Algorithms to identify the influential features affecting the price of Ford cars.

• Conducted a comprehensive analysis of car prices using various regression techniques to establish relationships between car attributes and pricing.
• Utilized Decision Tree, Random Forest, AdaBoost, Ridge, Lasso, and Support Vector Regression for predictive modeling.
• Evaluated model performance using R-squared (R2) values and Root Mean Square Error (RMSE).
• Identified the Random Forest Regressor as the top-performing model with an R2 of 0.93 and the lowest RMSE of 1265.
• Established the order of importance for features affecting car prices: year, mpg, price, and tax.

Project – Design of Experiments of Predicting Hatch

Simulation of experiments to identify the optimal sampling rate to ensure high-quality probability estimates using Excel.

Collaborated with Aviagen North America, a global poultry breeding corporation, to create a user-friendly egg hatching rate prediction tool. Applied statistical sampling and hypothesis testing to optimize estimations, resulting in cost reduction and minimal bird disturbances. Improved breeding stock quality and customer satisfaction in the poultry industry through advanced data analytics and statistical methodologies.

• Analyzed problems and worked with teams to develop solutions.
• Sorted and organized files, spreadsheets, and reports.
• Completed research, compiled data, updated spreadsheets and produced timely reports.
• Explored new technologies and approaches to streamline processes.