Articles

The project aimed to address the significant role of fuel prices in shaping the overall inflation landscape, given the crucial implications for economic policy-making and decision-making. By leveraging advanced data science techniques, we sought to enhance the accuracy and reliability of inflation forecasts, particularly in relation to the fuel index.

This project involved creating a data vault system for storing and analyzing medical imaging data obtained from Functional Near Infrared Spectroscopy (fNIRS). The system consisted of different layers, including staging, enterprise, data mart, and GUI layers. The staging layer processed and prepared the data for the subsequent layers, while the enterprise layer stored the data in a warehouse with version control and metadata management. The data mart layer facilitated querying of the stored data, presented in a star schema format. The GUI layer provided a visual interface to display and interpret the brain scan data as images.

This project aimed to predict the successful landing of the Falcon 9 rocket's first stage boosters, allowing SpaceX to offer competitive pricing for satellite launches through booster reuse. Data was collected, normalized, and analyzed using SQL, Python, and visualization techniques. Predictive models were built and evaluated, with the best model used to forecast future landing success.