ByteStorm: a multi-step data-driven approach for Tropical Cyclones detection and tracking

1. 1Collect and preprocess large datasets of weather and climate variables
2. 2Apply machine learning algorithms to identify patterns and features associated with Tropical Cyclones
3. 3Implement a multi-step tracking scheme to detect and predict the movement of Tropical Cyclones
4. 4Evaluate and refine the framework using performance metrics and comparison with traditional tracking schemes

Data scientists and researchers on a team can benefit from ByteStorm as it provides an efficient and accurate method for tracking Tropical Cyclones, while software engineers can implement and integrate the framework

💡 ByteStorm provides an efficient and accurate method for tracking Tropical Cyclones using a multi-step data-driven framework

🌪️ ByteStorm: a data-driven approach for detecting and tracking Tropical Cyclones