| Project Link | Area | Project Description |
|---|---|---|
| Maternal Health | Health | Analyzing maternal health data to identify top trends in maternal health, differences between states and how that different factors may affect the embryo health |
| Birth Metrics | Health | Analyzing natality 2022 data to identify trends in prenatal care, maternal behaviors, and their effects on newborn health |
| Project Link | Area | Project Description | Libraries |
|---|---|---|---|
| Hacker News Posts | Marketing | Analysing Hacker news users retentions best time to publish ... | Pandas |
| Financial Market Insights | Finance | leverages the Nasdaq Data Link API to extract and analyze financial data trends, providing insights into market behaviors and investment opportunities | requests, Pandas, Matplotlib |
| Predicting Bike Rentals | Marketing | This project predicts bike rentals using a rich dataset from Washington D.C.'s Bikeshare system, blending weather, seasonal data, and machine learning to forecast demand with precision. | Numpy, Pandas, Matplotlib, Sklearn |
| Credit Card Customer Segmentation | Finance | Sorting bank customers into groups to understand what they have in common and to help the bank keep them happy. | Pandas, Matplotlib, Seabron, Sklearn |
| Predicting Heart Disease | Health | The project employs a K-Nearest Neighbors classifier to predict the likelihood of heart disease in patients aiming to identify patterns and insights within patient data, such as age, sex, cholesterol levels, and exercise habits, to forecast heart disease outcomes with accuracy. | Pandas, Matplotlib, Seabron, Sklearn |