Chapter 21
Using Data Science to Describe and Predict Criminal Activity
In This Chapter
Talking about temporal data analysis
Using standard GIS solutions
Seeing how advanced spatial statistics fit in
Evaluating the limitations of the data science approach
In recent years, data science has been increasingly incorporated into criminological methodologies in a practice that’s been referred to as predictive policing. Predictive policing offers promising results, and law enforcement decision makers have high hopes that they can use predictive intelligence to help them formulate more effective tactical strategies. Judges hope to use predictive insights for support when deciding when to grant bail to suspects. Police agencies want to use the technology for improved offender monitoring. Consequently, there’s a very high demand for crime analysts who are skilled at using data science to build descriptive and predictive information products to support the decisions of law enforcement officials.
To practice data science in criminal analysis, you need to be skilled in GIS, data visualization, ...
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