Mobile-Price-Classification

This repository contains a machine learning model to classify mobile phones into different price categories based on their features. The dataset used for this project is the Mobile Price Classification Dataset from kaggle, which includes various attributes of mobile phones such as battery power, RAM, camera specs, and more, along with the corresponding price range.

Features:

Data Preprocessing: Cleaning and preparing the dataset for model training.

Exploratory Data Analysis (EDA): Visualizing and understanding the relationships between features.

Model Building: Implementing machine learning algorithms such as Decision Trees, Random Forest, and Logistic Regression.

Model Evaluation: Using metrics like accuracy, precision, recall, and F1-score to evaluate model performance.

Price Range Prediction: Classifying mobile phones into price categories (low, medium, high).

Technologies Used:

Python

Pandas

Scikit-learn

Matplotlib

Seaborn