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Data Cleaning of the Car Data set

In this project, you will be learning all the basics of machine learning, many libraries and modules in Python. Specifically, we will be learning algorithms for Data Analysis such as Polynomial Regression, Logistics Regression, Supervised Learning Techniques, KNN algorithm , Dendrograms etc. The application for the study is the Descriptive analytics of Car data after performing the Data Cleaning.

  • Mechanical
  • Automotive. Materials Engineering

duration
Duration :

1 month

projectfees
Project Fees :

INR 30,000

Benefits of this Project

In this project, you will be learning all the basics of machine learning, many libraries and modules in Python. Specifically, we will be learning algorithms for Data Analysis such as Polynomial Regression, Logistics Regression, Supervised Learning Techniques, KNN algorithm , Dendrograms etc. The application for the study is the Descriptive analytics of Car data after performing the Data Cleaning.

What will you do in this project?

Data cleaning that is replacing the Missing data with meaning full data point

Classification done of Car done based on the Price, brand , engine Location . Type of fuel used , Aspiration etc

Prediction of price for each brand of cars based on analysis

In this project, you will work on a Data cleaning using Python 

  • Understanding the Basics of ML & AI.
  • The various Data analytics module available in Python.
  • Data Wrangling ,i.e conversion of Raw data into useful data. 
  • Replacing the unavailable data with the Average of the Corresponding Data.
  • Doing the Descriptive analytics to thus Cleaned Data. 
  • Classification of Cars based on the various parameters.
  • Analysing the Trends of Pricing for various parameters such as Engine size, Fuel Used,  Power of the engine etc.

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Showing 1 of 3 projects

Project Highlights

The project is an advanced level project

Pre-requisites

Work with various Modules in Python

showcase

Data Cleaning of the Car Data set and Doing the descriptive analytics

This project focuses on the Data cleaning that is removing the unavailable data with meaningful data set. ML & AI helps to construct the Correlation Matrix to choose the Dominant parameters in the Data set. The Dominant characters are used in Predicting the Price of the Vehicle.