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Build a Regression Model to Predict the Fare Amount for Uber Passengers

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Build a Regression Model to Predict the Fare amount for Uber Passengers.

Problem Statement

A fare calculator helps a customer in identifying the fare valid for the trip. They are often used by passengers who are new to a city or tourists to get an estimate of travel costs. You are provided with a dataset with features like fare amount, pickup and drop location, passenger count, and so on.

Following actions should be performed:

  1. Understand the type of data.
  2. Identify the output variable.
  3. Identify the factors which affect the output variable.
  4. Check if there are any biases in your dataset.
  5. Count the null values existing in columns.
  6. Remove the null value rows in the target variable.
  7. Perform train test split.
  8. Predict the accuracy using regression models.
  9. Check and compare the accuracy of the different models.

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