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Clean and extract features from a large, scrapped data set from the Palestinian market. Deploying ML Pipeline

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car-price-prediction

Problem Statement

To understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting the pricing of cars in the Palestinian market. The company wants to know the following:

  • Which variables are significant in predicting the price of a car
  • How well do these variables describe the price of a car Based on various market surveys

I'll utilize a large data set scrapped with different types of cars across the Palestinian market.

Bussiness Goal

We are required to model the price of cars with the available independent variables. It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market.

This Notebook will cover the following -

  1. Data cleaning
  2. Exploratory Data Analysis
  3. Feature Engineering
  4. Feature selection
  5. Data Modelling and evaluation

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Clean and extract features from a large, scrapped data set from the Palestinian market. Deploying ML Pipeline

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