SP-2 Red Data Mining and AI

This project focuses on leveraging artificial intelligence (AI) and data analytics to derive insights from crime data across the United States. Specifically, the Federal Bureau of Investigation's (FBI) National Incident Based Reporting System (NIBRS). The team aimed to develop an AI model capable of analyzing this extensive crime data to identify patterns, assess risk factors, and predict future criminal activities. The developer's utilized clustering algorithms and advanced data analysis techniques to enhance the efficiency and effectiveness of crime analysis.

Key Components:

• Data Collection and Processing: Data from the FBI's Crime Data Explorer was collected, processed, and standardized for analysis. Geographic and temporal information is crucial for identifying trends and patterns.

• AI Model Development: The AI model is designed to analyze crime data effectively, identify high-risk regions, and provide meaningful insights.

• Challenges and Solutions: The project encountered challenges in data acquisition and model development, leading to adaptations and innovative solutions to ensure project success.

Links:

• GitHub 

Statistics:

• Number of lines in code: 2,486 (combined from Model and Database)

• Number of components in project: 8

Please refer to the table of contents for detailed project documentation.