Crime-Prediction-and-Analysis-Using-Machine-Learning

This machine learning research aims to identify and analyze crimes that take place in urban areas. Columns including the date of occurrence, month, reporting date, neighborhood, kind of offense, and MCI (major crime indicators) are included in this dataset. This would make it easier to identify which neighborhoods are risky and need police attention. Additionally, it would add to the general public's understanding for their personal safety and well-being. Our study uses a set of real-world crime datasets to forecast crime and identify temporal and spatial criminal hotspots. We shall make an effort to identify the most probable crime scenes and the times at which they occur most frequently.Furthermore, we will forecast what kind of crime might happen next in a given area at a given time. Lastly, by integrating our findings on a specific crime dataset with its demographic data, we want to present an analysis research.