Predicting Placement in Campus Recruitment • Built a machine learning model to predict student placement outcomes, achieving 91.45% accuracy. • Reduced error margin by 10% through iterative optimization and testing.
Classification of Alzheimer’s Disease Using CNN • Developed a convolutional neural network (CNN) to classify Alzheimer’s disease, achieving 97% accuracy. • Published findings in SPRINGER journals and presented at international conferences.
Exploratory Analysis of Job Market Trends in Australia • Performed data wrangling, cleaning, and visualization using Python, Tableau, and SQL to provide insights into job vacancies and trends in the Australian market. • Leveraged big data technologies like Apache Spark for efficient data processing and analysis of large datasets.