Bu analiz, insanların mutluluğu ve ülkeleri arasındaki bağlantıyı değerlendirecektir.
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Updated
May 25, 2024 - Python
Bu analiz, insanların mutluluğu ve ülkeleri arasındaki bağlantıyı değerlendirecektir.
Collaborative visualization task
As a Data Analyst Intern at Intern Career my task is to create a Power BI dashboard that provides a comprehensive overview of global terrorism trends and patterns.
This repository contains an Exploratory Data Analysis (EDA) on the Global Terrorism Dataset. The EDA was performed using Python's Pandas, NumPy, Matplotlib, and Seaborn libraries to identify the hot zones of terrorism and gain valuable insights from the dataset.
In an era marked by global security challenges, the "TAFRAS" emerges as a cutting-edge solution to tackle the ever-evolving threat of terrorism. The project is grounded in the urgent need for predictive systems that can anticipate, assess, and mitigate potential terrorist activities.
A comprehensive analysis of the GTD, to uncover global terrorism patterns, trends, and impacts through data-driven analysis. Involves rigorous analysis of most used attack & weapon types; favourite targets; yearly distribution of casualties, no. of attacks, success rates, and more - both holistic and for specific countries and terror organizations
The Spark Foundation Task-------->The project analyses and visualises global terrorist attacks over the time frame of 1970 to 2019. Points out and analyses trends of over 2,00,000 terror attacks, their attackers and studies various other features
Global Terrorism Database Interactive Dashboard
Exploratory Data Analysis on dataset Global Terrorism.As a defence or security analyst we have to find hot zone of terrorism.
Analysis and Visualization for the Global Terrorism Dataset including ANOVA tests volcano plots and Topological Data Analysis applications https://www.start.umd.edu & https://www.kaggle.com/START-UMD/gtd#globalterrorismdb_0718dist.csv
Creating a dashboard to generate plots and infographics based on the Global Terrorism Database.
The project analyses and visualises global terrorist attacks over the time frame of 1970 to 2019. Points out and analyses trends of over 2,00,000 terror attacks, their attackers and studies various other features
This project is an attempt to use START Global Terrorism Dataset to target a regression problem and identify region for probable terror attack. Predict number of casualties in a terrorist attack, based on a custom metric.
This is an information visualization project of Global Terrorism Database with Yingrong Mao.
A visualization of k-means clustering on terrorist attack locations
A web-based visualization of the Global Terrorism Database using D3.js.
This repository presents analyses conducted in R on The Troubles using the Global Terrorism Database
Used the Global Terrorism Database to Explore Features of Suicide Bombings
This project used machine learning to understand characteristics of terrorist groups that engage in suicide bombings.
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