Implement machine learning models (Decision Tree, Support Vector Machine, Neural Network) from the Scikit-Learn library to predict if a given terrorist attack will be successful, resulting in 92% accuracy.

The goal of this project is to develop a predictive model that can identify potential locations for mass shooting events based on certain indicators, such as mental health history and signs of being in a crisis. The primary objective is to explore the relationship between these indicators and the likelihood of a mass shooting event occurring.

In an era dominated by data-driven decision-making, the role of data scientists carries significant weight. Armed with the ability to extract profound insights from vast datasets, they empower organizations to fine-tune their operations, craft personalized user experiences, and forecast future trends with remarkable accuracy...