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The goal of this machine learning project in R is to build a predictive model that can predict the total travelling time of 442 taxis running in the city of Porto based on their partial trajectories. This predictive framework will be used to enhance the efficiency of electronic taxi dispatching systems in Porto. You will use the taxi trajectory dataset from 01/07/2013 to 30/06/2014 containing the trajectories for all the 442 taxis running in the city of Porto.
Forecast the business for the upcoming years by Exploring Hidden Trends, Calculating Machine Productivity , Extrapolation and Assumptions and Summarizing Answers through Visualizations.
In this project, we are going to talk about insurance forecast by using regression techniques.
Using this Kaggle dataset, you will explore which type of employees make less or more money, or which employees get normal pay hikes and promotions.