Mileage-Optimization

Building Fuel Efficient Cars

Project Introduction and Scope

In today's world, sustainable choices are paramount to combat environmental challenges and reduce carbon footprints. As part of my exploration into sustainable living, I have taken on a project to assist a prominent car manufacturer, known for its large automobiles, in designing energy-efficient vehicles that align with eco-conscious consumers' preferences. The objective of this project is to utilize data analysis and machine learning techniques to identify the key attributes that contribute to higher gas mileage (miles per gallon or MPG), enabling the development of automobiles that promote sustainability.

Scope of the Project:

Part 1 - Data Cleansing:

In the initial phase of this project, we will focus on data cleansing techniques to ensure that the dataset used for analysis is of the highest quality. This involves the thorough cleaning and preprocessing of the data to remove any inconsistencies, missing values, or outliers that might adversely affect the modeling process. We will detail the data cleansing process and explain the rationale behind each decision made during this phase.

Part 2 - Linear Regression Modeling:

In the second part of the project, we will construct a linear regression model to accurately predict the MPG of vehicles based on their attributes. This model will serve as a crucial tool in understanding the relationship between various vehicle characteristics and fuel efficiency. We will discuss the significance of these attributes and how they can inform the design of sustainable, fuel-efficient cars that contribute to eco-friendly transportation.

Part 3 - Model Optimization:

To enhance the predictive performance of our model, we will implement step-wise feature selection technique. This part will include a comparison between the optimized model and the baseline model from Part 2, highlighting the improvements achieved through the selection technique.

Part 4 - Achieving the Goals:

In the final phase, we will evaluate the model's ability to meet the specified goals. We will provide an explanation of whether the model can effectively predict MPG and contribute to the development of sustainable, environmentally-friendly vehicles. Additionally, we will identify and discuss the attributes, limited to no more than two, that have the most significant impact on achieving higher MPG, shedding light on which aspects should be prioritized during the automobile design process to promote sustainability.

This project aligns with the growing emphasis on sustainable choices and aims to provide valuable insights and practical solutions for designing eco-friendly vehicles. By combining data analysis, machine learning, and a commitment to sustainability, we aim to address the challenges faced by the automotive industry and contribute to a greener future.