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Taxi Trip Time Prediction using Regression, Numpy, Scipy in R

Predict the total travel time of taxi trips from their initial partial trajectories.
4.74.7

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What will you learn

  • Numpy
  • Pandas
  • Scipy
  • Scikit
  • Matplotlib
  • Advance Regression Algorithm
  • Continuous Data

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Prerequisites

  • Programming Language used: R

Project Description

The goal of this data science project 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. 

 

Instructors

 
Jeeban

Senior Statistical Analyst

"I enjoy 3 things in Analytics - Machine Learning, Image/Video Processing, Natural Language Processing."