🔋 EV Range Predictor

A Machine Learning web application that predicts the driving range of electric vehicles (EVs) using vehicle specifications and battery-related features.

---

🚀 Live Demo

👉 https://ev-range-predictor-42qy9pui3dgxcwcujynsea.streamlit.app/

---

📌 About the Project

The EV Range Predictor uses a trained machine learning pipeline to estimate how far an electric vehicle can travel on a single charge. The model is trained on EV specifications data and deployed using Streamlit for an interactive user experience.

---

⚙️ Features

• 🔢 Input EV specifications
• 📊 Predict estimated driving range
• ⚡ Fast and simple UI with Streamlit
• 🤖 Pre-trained ML pipeline for predictions

---

🧠 Tech Stack

• Python
• Streamlit
• Scikit-learn
• Pandas & NumPy

---

📂 Project Structure

EV-Range-Predictor/
│── app.py                         # Streamlit web app
│── pipe.pkl                       # Trained ML pipeline model
│── electric_vehicles_spec_2025.csv.csv  # Dataset
│── Predict-EVRange.ipynb          # Model training notebook
│── Test_EV_range.ipynb            # Testing notebook
│── requirements.txt               # Dependencies
│── README.md                      # Project documentation

---

🛠️ How It Works

1. User inputs EV specifications
2. Input data is processed using the trained pipeline
3. Model predicts the driving range
4. Result is displayed instantly

---

▶️ Run Locally

git clone https://github.com/your-username/ev-range-predictor.git
cd ev-range-predictor
pip install -r requirements.txt
streamlit run app.py

---

📊 Dataset

The dataset contains electric vehicle specifications such as battery capacity, efficiency, and other features used to train the model.

---

📸 Screenshots

---

📬 Contact

Feel free to reach out for feedback or collaboration! Gmail:- goyalmayank492@gmail.com