Terrorism has stricken fear in the hearts of many people across states and nations. To predict future patterns and gain past insights, in this report we aim to analyse the GTD dataset for various terrorist attacks and try to incorporate meaningful inferences from it along with bringing new novel pat- terns and relations undiscovered till now using various machine learning models like random forest classifier,bagging,k-NN,ANN after applying some initial cleaning and exploratory analysis on the data using classic visualising techniques like wordcloud, heat maps,geographical graphs and more.
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