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EV Range Prediction

This project aims to predict the driving range of electric vehicles based on their key specifications, primarily weight and battery capacity.

Dataset

  • Source: Data was collected using the 'Web Scraper' Chrome extension from EV Database.
  • Scope: Includes 44 different Tesla models.

Methodology

  • Data cleaning and preprocessing
  • Exploratory Data Analysis (EDA)
  • Linear regression modeling
  • Model evaluation using R²

Results

  • R² (Train): 0.85
  • R² (Test): 0.81

The model demonstrated good generalization with minimal overfitting. Battery capacity showed a strong positive impact on range, while vehicle weight had a negative correlation.

Skills Applied

  • Data collection and scraping
  • Data cleaning and visualization
  • Statistical analysis and machine learning (linear regression)
  • Python, pandas, matplotlib, scikit-learn

Author

Designed and developed by sheydakarimabadi – an industrial designer exploring the intersection of AI and product design.

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