Fixes #779 Car Mileage Prediction model

Prediction Models/Car_Mileage_Prediction/Readme.md

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+# Car Mileage Prediction Model
+
+This repository contains a machine learning model that predicts car mileage based on various car attributes. The model uses supervised learning to analyze historical data and generate predictions of mileage (miles per gallon) for different types of vehicles under varying conditions.
+
+## Table of Contents
+- [Introduction](#introduction)
+- [Problem Statement](#problem-statement)
+- [Model Overview](#model-overview)
+- [Data](#data)
+- [Installation](#installation)
+- [Usage](#usage)
+- [Results](#results)
+
+## Introduction
+
+Predicting car mileage is a complex task influenced by numerous factors like vehicle type, engine size, weight, and driving conditions. This project aims to develop a machine learning model that can predict the fuel efficiency of various vehicles to assist users in making more informed choices regarding fuel economy.
+
+## Problem Statement
+
+Estimating car mileage is affected by several factors:
+- **Data Quality**: Inconsistencies and gaps in the data can reduce prediction reliability.
+- **Feature Engineering**: It is critical to identify features that have the most significant impact on fuel efficiency.
+- **Generalization**: Ensuring the model’s accuracy across a wide range of car models and engine types.
+
+## Model Overview
+
+The model uses supervised machine learning methods to predict fuel efficiency. Several algorithms, such as linear regression, decision trees, and ensemble methods, are explored to determine which yields the best results. The following features are considered to impact car mileage:
+- Vehicle attributes (make, model, year)
+- Engine characteristics (engine size, horsepower)
+- Weight and transmission type
+
+The model is trained on historical data to predict miles per gallon (MPG) based on these features.
+
+## Data
+
+The dataset includes:
+- **Vehicle Attributes**: Make, model, and year of manufacture.
+- **Engine Characteristics**: Engine size, horsepower, and fuel type.
+- **Mileage Data**: Observed fuel efficiency in miles per gallon (MPG).
+
+Data should be placed in the `data/` folder as a CSV file for easy access by the model.
+
+## Results
+Model performance is measured using accuracy metrics such as Mean Absolute Error (MAE) and Mean Squared Error (MSE). Experimenting with different features and hyperparameters can further improve accuracy.
+
+