The latest articles on DEV Community by Zaryab Ahmad (@zaryab_ahmad_2fe968e3216b). https://dev.to/zaryab_ahmad_2fe968e3216b https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3561074%2F87d5fb4a-474a-462f-9a43-9b756114d89c.jpg https://dev.to/zaryab_ahmad_2fe968e3216b en Zaryab Ahmad Sun, 12 Oct 2025 19:56:02 +0000 https://dev.to/zaryab_ahmad_2fe968e3216b/car-price-prediction-a-complete-ml-project-7a1 https://dev.to/zaryab_ahmad_2fe968e3216b/car-price-prediction-a-complete-ml-project-7a1 <h2> 📊 Project Overview </h2> <p>Built a machine learning model to predict car prices using vehicle specifications and features.</p> <h2> 🔧 Data &amp; Preprocessing </h2> <ul> <li> <strong>205 cars</strong> with 16 features (engine specs, dimensions, fuel type, etc.)</li> <li>Encoded categorical variables using Label Encoding</li> <li>Scaled features with StandardScaler for better model performance</li> </ul> <h2> 🤖 Models Compared </h2> <div class="table-wrapper-paragraph"><table> <thead> <tr> <th>Model</th> <th>Training Score</th> <th>Testing Score</th> </tr> </thead> <tbody> <tr> <td>Linear Regression</td> <td>84.5%</td> <td>79.4%</td> </tr> <tr> <td>Decision Tree</td> <td>91.7%</td> <td>85.3%</td> </tr> <tr> <td>SVR</td> <td>-10.8%</td> <td>-9.9%</td> </tr> <tr> <td><strong>Random Forest</strong></td> <td><strong>98.2%</strong></td> <td><strong>95.6%</strong></td> </tr> </tbody> </table></div> <h2> 🏆 Results </h2> <ul> <li> <strong>Random Forest</strong> performed best with 95.6% accuracy</li> <li> <strong>Mean Absolute Error</strong>: $1,313</li> <li>Model can predict prices for new car specifications</li> </ul> <h2> 💡 Key Insights </h2> <ul> <li>Ensemble methods (Random Forest) handle complex patterns better</li> <li>Engine specs and dimensions are major price factors</li> <li>Proper data preprocessing is crucial for success</li> <li>Some models (like SVR) may not suit all dataset types</li> </ul> <h2> 🚀 Takeaway </h2> <p>Random Forest proved ideal for this regression problem, balancing accuracy and robustness while handling the complex relationships in car pricing data.</p> <h1> ai #python #datascience #machinelearning </h1> ai beginners python datascience