Built a model using CNNs (AlexNet, ResNet18) to classify normal, COVID-19, and viral pneumonia cases from chest X-ray images. Utilized Python and PyTorch with advanced preprocessing techniques. Achieved over 95% accuracy, providing a potential diagnostic tool for healthcare professionals
Skills: Deep Learning ยท PyTorch ยท Healthcare Analytics ยท AI for Healthcare ยท Model Evaluation
This analysis predicts *median_house_value* using features like location, housing age, and income. Key findings show that *median_income* has the strongest correlation with house value.
This interactive map visualizes:
Colleges (Public vs. Private) based on their admission rates and undergraduate population.
Major cities with a population greater than 50,000, highlighting proximity to these colleges.
This project helped me enhance my skills in data merging, geographic visualizations, and interactive dashboards
"Developed a sales forecasting model using ARIMA to predict future sales trends based on historical data. Optimized the model to achieve accurate forecasting, aiding in strategic decision-making and inventory management."
๐ The goal was to identify key factors contributing to dropouts and provide actionable insights to improve student retention.