Predicting Price Range of Mobile Phones.
This project is an educational endeavor completed using Kaggle datasets. The goal was to perform models to predict price range of mobile phones and clessify them based on their features.
Utilized the Mobile Price Classification dataset from Kaggle (link to dataset).
Bob has started his own mobile company. He wants to give tough fight to big companies like Apple,Samsung etc.
He does not know how to estimate price of mobiles his company creates. In this competitive mobile phone market you cannot simply assume things. To solve this problem he collects sales data of mobile phones of various companies.
Bob wants to find out some relation between features of a mobile phone(eg:- RAM,Internal Memory etc) and its selling price. But he is not so good at Machine Learning. So he needs your help to solve this problem.
In this problem you do not have to predict actual price but a price range indicating how high the price is
The project includes data analysis (EDA), models training, and evaluation.
Conducted EDA to understand feature distributions and correlations. Implemented various machine learning models including decision trees, random forest, logistic regression, gradient boosting and linear neural networks.