![]() ![]() When I downloaded it for my project, it contained 164116 observations of 20 variables. It is a dynamic dataset, it is updated every workday, including refining information about previously reported incidents. It contains data about all accidents with reported damage more than 1ooo dollars or involving fatalities, injuries or evidence of drug or alcohol use for the past 5 years. The main source of accidents data for this project is the traffic accident dataset maintained by the City and County of Denver Police Department. So, in this project, I would like to assess the validity of these claims. In casual conversations and on social media people often mention at least four stereotypical reasons for growing number of accidents – explosive population growth due to out of state migration, alcohol consumption, recreational marijuana use and drugs in general, and everchanging Colorado weather. So, I came up with this exploratory project its main goal is to analyze car accident data for the last 5 years in order to try to find variables that can be used as predictors for future car accidents. While almost everyone agrees that human costs in terms of lost lives and injuries are unacceptable and that economic consequences, for example, high car insurance premiums, are felt by many, there is no consensus on what factors are driving this trend. The number of car accidents in Denver has been steadily increasing over the past few years. Predicting Denver Traffic Accidents using machine learning techniques in Python Project Overview ![]()
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