Predicting Terrorist Attacks and Analyzing Crime Incidents in Nigeria Using Machine Learning

Local Chapter Enugu, Nigeria Chapter

Coordinated byNigeria ,

Status: Completed

Project Duration: 17 Jun 2023 - 29 Jul 2023

Open Source resources available from this project

Project background.

According to Wikipedia, Nigeria is considered to be a country with a high level of crime, ranking 17th among the least peaceful countries in the world, and during the first half of 2022, almost 6,000 people were killed by jihadists, kidnappers, bandits, or the Nigerian army.

Being able to tackle the rate of crime in the country is a big plus to the security of the nation. The ability of the security agency to have a clear understanding of the distribution of different crimes committed and also able to anticipate/predict possible crime outbursts will go a long way to tackling the security challenges of the nation.

The problem.

The problem this project is targeted to solve is to help the security agencies to mitigate the rate of crime committed in the country by giving the security agencies reasonable insight into the distribution of crime committed in Nigeria, and also enable them to anticipate possible crime and location of the crime, in order to be able to make adequate security checks and take the necessary security measures.

Project goals.

The major goals of this project are: - Analyze the crimes committed in Nigeria. - Build a predictive model to predict the type of crime to be committed in a given time and location.

Project plan.

  • Week 1

    Data collection and cleaning of data.

  • Week 2

    Exploratory Data Analysis and Data Preprocessing

  • Week 3

    Model building

  • Week 4

    Hyperparameter tunning and improvement of model accuracy.

  • Week 5

    Deployment of model.

Learning outcomes.

The learning outcomes in this project are data collection, data analysis, predictive supervised machine learning model building, and model deployment.

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