Fuel Efficiency (MPG) Prediction Using Machine Learning - Couverture souple

Sharma, Abhishek ; Joshi, Abhishek ; Waghela, Mohit

9786209635007: Fuel Efficiency (MPG) Prediction Using Machine Learning

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ISBN 10 : 6209635008 ISBN 13 : 9786209635007

Editeur : LAP Lambert Academic Publishing, 2026

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�diteur: LAP Lambert Academic Publishing
Date d'�dition: 2026
Langue: anglais
ISBN 10: 6209635008
ISBN 13: 9786209635007
Reliure: Broch�
Nombre de pages: 56
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Fuel Efficiency (MPG) Prediction Using Machine Learning

Sharma, Abhishek; Joshi, Abhishek; Waghela, Mohit

Edit� par LAP Lambert Academic Publishing, 2026

ISBN 10 : 6209635008 ISBN 13 : 9786209635007

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Fuel Efficiency (MPG) Prediction Using Machine Learning

Sharma, Abhishek; Joshi, Abhishek; Waghela, Mohit

Edit� par LAP LAMBERT Academic Publishing, 2026

ISBN 10 : 6209635008 ISBN 13 : 9786209635007

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Fuel Efficiency (MPG) Prediction Using Machine Learning

Abhishek Sharma

Edit� par LAP LAMBERT Academic Publishing M�r 2026, 2026

ISBN 10 : 6209635008 ISBN 13 : 9786209635007

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch. N� de r�f. du vendeur 9786209635007

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Fuel Efficiency (MPG) Prediction Using Machine Learning (Paperback)

Abhishek Sharma

Edit� par LAP Lambert Academic Publishing, 2026

ISBN 10 : 6209635008 ISBN 13 : 9786209635007

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Paperback. Etat : new. Paperback. Fuel efficiency plays a crucial role in automotive design, environmental sustainability, and performance analysis. This project presents a Machine Learning approach for predicting Miles Per Gallon (MPG) using vehicle features from the well-known Auto MPG dataset available at the UCI Machine Learning Repository.The dataset undergoes pre-processing steps including handling missing values, converting data types, and selecting key numerical attributes. Two predictive models-Linear Regression and Random Forest Regressor-are implemented and evaluated using standard regression metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R2 score. The Random Forest model performs significantly better, indicating its strength in capturing nonlinear patterns in vehicle characteristics.The study highlights the potential of Machine Learning to support automobile efficiency analysis and fuel consumption forecasting. Future enhancements may include model tuning, advanced algorithms, real-time prediction systems, and deployment through a web interface. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9786209635007

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Fuel Efficiency (MPG) Prediction Using Machine Learning

Abhishek Sharma

Edit� par LAP LAMBERT Academic Publishing M�r 2026, 2026

ISBN 10 : 6209635008 ISBN 13 : 9786209635007

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Fuel efficiency plays a crucial role in automotive design, environmental sustainability, and performance analysis. This project presents a Machine Learning approach for predicting Miles Per Gallon (MPG) using vehicle features from the well-known Auto MPG dataset available at the UCI Machine Learning Repository.The dataset undergoes pre-processing steps including handling missing values, converting data types, and selecting key numerical attributes. Two predictive models-Linear Regression and Random Forest Regressor-are implemented and evaluated using standard regression metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R score. The Random Forest model performs significantly better, indicating its strength in capturing nonlinear patterns in vehicle characteristics.The study highlights the potential of Machine Learning to support automobile efficiency analysis and fuel consumption forecasting. Future enhancements may include model tuning, advanced algorithms, real-time prediction systems, and deployment through a web interface.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 56 pp. Englisch. N� de r�f. du vendeur 9786209635007

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