Supervised ML- Built a Multi-Class classification model to find the relation between features of a mobile phone(RAM, Internal Memory etc) and its selling price. Model will predict the price range indicating how high the price is.

I have implemented a Mobile Price Prediction using different Machine Learning Algorithms. This project will classify the price range of the mobile price. The price ranges from 0-3. We’ll discuss the price range in the dataset. Now I have trained a mobile price classification using 3 ML algorithms. This model classifies the range of the mobile based on the different parameters like from camera, touch screen, cores, battery, clock speed, internal memory, battery capacity, etc. After training the model using 3 algorithms, I compared all the models using the graph.

A classification model to predict whether price range of mobile based on certain specifications

Mobile phone purchase prediction project. Classification model based on phone features to recommend the best price range/category for customers.

Mobile Price Range Prediction: Use sales data to build a classification model for mobile phone price ranges. Features include battery power, camera, memory, and connectivity. Split data, apply logistic regression, KNN, SVM (linear and rbf), and evaluate using confusion matrices. Select the most accurate model.

Problem statement: Create a classification model to predict whether price range of mobile based on certain specifications ->At first we check any null values is there are not if any we will modify or remove ->Then visualization the data using differnt attribute which are correaltion to price attribute ->After we divide the data set into train and t

Mobile Price Classification classify mobile price range

This project is dedicated to developing a classification system that categorizes mobile devices into different price ranges. By employing ML techniques and mobile specifications, this project helps consumers make informed decisions when purchasing mobile phones, ensuring they find the right device that fits their budget and requirements.

📱Machine learning project that classifies smartphones into price ranges using their specifications, with Logistic Regression selected as the final model for its high accuracy and interpretability.

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Applied Machine Learning - submission task Machine Learning predict analysis

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Classification Project: Mobile Price Range Prediction

The dataset used for this purpose has taken into consideration 21 different parameters for predicting the price of the phone . Random Forest Classifier, Support Vector Machine , Decision Tree, Gradient Boosting classifier, K-nearest Neighbour Classifier and XG Boost classifier have been used primarily

Classification Project on Mobile Price Range Prediction

Mobile price range predication classification project ML

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Mobile Price Range Prediction-EDA-Supervised ML-Classification

Multi-class classification model for mobile price range.

Classification Models Applied: Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, Random Forest, Naive Bayes. Each model is evaluated based on: Accuracy Score, Confusion Matrix,

Predicting mobile price range using supervised learning classification technique.

Classification of Mobile phones into price ranges based on technical specifications

Implemented some popular classification algorithms to predict the price range of mobile phones

Mobile price classification is a model to predict price range of mobile based on certain specifications using machine learning techniques.

Create a classification model to predict whether price range of mobile based on certain specifications

The Devices Price Classification System is designed to predict the price range of mobile devices based on their specifications

In this Jupyter Notebook we discuss about the ML Classification Project on Mobile Price Range Prediction

In the Mobile Price Classification project, I built a predictive model to categorize mobile phones into different price ranges based on their features by applying machine learning techniques.

Discover my GitHub repository for mobile price classification. Explore projects, code samples, and machine learning algorithms to accurately classify mobile phones based on their price ranges. Ideal for data enthusiasts and mobile industry professionals. Start exploring now!

A machine learning project that predicts the price range of mobile phones based on key features such as RAM, screen resolution, battery power, internal memory, and more. This project utilizes classification techniques to analyze and categorize mobile phones into predefined price ranges.