ML - Mobile price prediction Classification project #almabetter #machinelearning #codeandcombat

In this video, we summarize a machine learning project analyzing factors influencing mobile phone price ranges. Using a dataset with 21 variables, we cleaned data, handled missing values, and performed EDA. Key findings include a strong correlation between price range and RAM, battery power, and pixel quality. Surprisingly, screen size and primary camera megapixels had little impact. After hypothesis testing and outlier handling, we built models like logistic regression, random forest, and XGBoost. The best results came from logistic regression and XGBoost with hyperparameter tuning. Watch to learn more about our insights! Stay tuned for more exciting projects and insights on our channel! Don't forget to like, subscribe, and hit the notification bell to stay updated. My GitHub profile : https://github.com/data-enthusiast-shubhs This project's GitHub Repository -: https://github.com/data-enthusiast-shubhs/AlmaBetter_ML_Mobile_Price_prediction_Classification_Project.git My LinkedIn - https://www.linkedin.com/in/shubham-oli-12911so/