Mobile phone price dataset This is Python script which scrape the GSMArena website mobile phones specification and save in the csv format files Jul 22, 2022 · A price prediction study is conducted on different machine learning algorithms using a dataset of phone prices and features from Kaggle, 4 different models with 20 features are tackled and the highest value is obtained from Support Vector Machine with an accuracy value of 0. In In this competitive mobile phone market you cannot simply assume things. It surpassed the previous highest average selling price of 254 U. Int J Adv Res Sci Technol. Crowdsourced original images of a wide variety of mobile phones. Keywords: Mobile Price Prediction, Machine Learning, Algorithm, KNN. This project demonstrates a mobile price prediction model using four classification algorithms: Random Forest, Gaussian Naive Bayes, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The aim is to predict the price range of mobile phones based on various features and specifications Jul 22, 2022 · A price prediction study is conducted on different machine learning algorithms using a dataset of phone prices and features from Kaggle, 4 different models with 20 features are tackled and the highest value is obtained from Support Vector Machine with an accuracy value of 0. by Success. Get the new arrivals first and find the great deals for the best android phones prices. The developed model is then used to predict the price range of the new mobile phone. employed the Bagging algorithm and However, estimating the price of our mobile phones remains a challenge. Feb 23, 2022 · Classification Model for Mobile Phone Price Range. The dataset consisted of various features related to mobile phones such as battery capacity, RAM, internal memory, camera quality, and other hardware specifications. Jun 12, 2024 · The dataset includes mobile phones manufactured or . Its Denotes name of the mobile phones and Brands. 1109/AISP57993. The 'Mobile Price Data' dataset is designed for training classification models to predict mobile phone prices. Contribute to Coffeec0de/Mobile_phone_prices_dataset development by creating an account on GitHub. The price ranges from 0-3. July 2022. The objective is to analyze the device characteristics and explore their influence on the device price. com is used to evaluate methods. csv file contains a dataset without a label column which will be added a 'price_range' column containing mobile price prediction according to the condition previously mentioned. (AI-generated) Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. The Mobile Price Prediction dataset is a comprehensive collection of mobile phone specifications and prices across various brands. - ditekunov/mobile-phones-price-prediction. To eliminate this burden, we have investigated different machine learning algorithm on guessing telephone prices. We used a dataset that contains mobile phones information, and there was a number of factors that influence the classification of mobile phone price. Nowadays, mobile phones are selling and purchasing in a huge number. Learn more. Moreover, each mobile phone comes with a set of features and specifications such as the RAM memory, CPU, front and back camera quality, and so on. It includes two hidden layers (8 and 4 neurons). Three machine learning algorithms namely Support Vector Machine (SVM), Random Forest Classifier (RFC), Logistic The goal of this project is to develop classification model for dataset that hold specifications of 2000 mobile phones attempt to predict best price ranges by applying various machine learning algorithm. OK, Got it. ai This dataset is an extremely challenging set of over 3000+ original Mobile Phone images captured and crowdsourced from over 1000+ urban and rural areas, where each image is manually reviewed and verified by mobile price prediction. S. mm, online store. This project will classify the price range of the mobile price. These features include battery capacity (measured in mAh), Bluetooth availability (represented as "Blue dataset. The various features and information can be used to predict the price range of a mobile phone. But people fail to link those factors with the price of mobile phones; in this case, this paper is aimed to figure out the problem by using machine Specifications and Prices of various mobile phones Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Nov 1, 2021 · People fail to make correct decisions, due to the non-availability of necessary resources to cross-validate the price. In today's diverse mobile market, finding the perfect phone within budget can be daunting. - farhan39/Products-Data-Analysis Compare the lowest and best price for mobile phones to buy from the largest price list in Sri Lanka. But people fail to link those factors with the price of mobile phones; in this case, this paper is aimed to figure out the problem by using machine With the rise of online marketplaces, buying and selling used phones has become more accessible. dollars) Premium Statistic Breakdown of mobile phone owners in India 2023, by gender and type Jul 30, 2024 · The average selling price of smartphones in India was around 255 U. We have one available in the Data folder, data. ai. Jan 14, 2025 · Curated list of all the latest Motorola smartphones with specifications, prices and benchmarks in chronological order. Jul 10, 2024 · Swathi MS, Sajja DC, Kolavennu S, Mulagandla RR, Ale S. The task is to perform exploratory data analysis (EDA) on the dataset to understand the underlying relationships and patterns in the data, and then build a regression model to Mobile Phone Dataset: Training Data for Predicting Mobile Models 📱 Mobile Price - Intermediate 🗃️ Dataset | Kaggle Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. The "Mobile Price Classification" dataset which is taken from Kaggle. Mar 5, 2021 · The price of a product is the most important attribute of marketing that product. Kukreti A. Mobile Phone Price Prediction In this project, we are going to explore and analyze a dataset which contains specifications of two thousand mobile phones and try to predict optimum price ranges for a list of mobile phones in the market by applying various machine learning algorithms such as logistic regression, decision tree, random forest and k-nearest neighbors(knn). Find the Latest Xiaomi mobile phones price in Bangladesh 2025. Extensive research is recorded in selecting best features. Using the data given we had to build a model for predicting the price range of a mobile phone. Additionally, the project involves implementing different classification models. The dataset consists of a nearly 2000 data entries of mobile phone features (RAM, size, etc. With the development of technology In general each mobile phone can be assigned to one of these four price ranges: low, medium, high, and very high. Predicting the price of a used phone accurately is a challenging task due to factors such as the phone's age, brand, model, condition, and market demand. Explore and run machine learning code with Kaggle Notebooks | Using data from Flipkart Mobiles Dataset Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. - PratikGarai/Mobile-Phone-Dataset-Analysis Mar 17, 2023 · (DOI: 10. 02. Int J Mech Eng. Factors such as brand, internal memory, wifi, battery power, camera and availability of 4G are now modifying consumers' decisions on buying mobile phones. Feb 7, 2024 · Mobile phone user statistics show that, as of 2023, 98% of all adults aged 16-24 in the UK have a smartphone. It is a classification problem where the target take four class: 0 to 3. 0 (low cost) 1 (medium cost) 2 (high cost) 3 (very high cost) The dataset is available here. Leveraging mobile price classification dataset to predict price range of mobile phones - jherford/mobile-phone-prices Feb 10, 2023 · In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the price range of a mobile phone. Select the most accurate model. Amazon Phone Data: Prices, Ratings & Sales Insight | Kaggle Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Firstly, all values Mar 19, 2024 · to mobile phones. In this paper eight classifiers including SVC, KNN, ANN, RF, Decision Tree, Naive Bayes, Linear Discriminant Analysis, Logistic clients in selecting mobile phones based on their budget and desired features. 9616. 2. But people fail to link those factors with the price of mobile phones; in this case, this paper is aimed to figure out the problem by using machine This dataset is collected by DataCluster Labs, India. We used a dataset that contains mobile phones information, and About. A. Brand me — This is first feature of our dataset. Kofi Nti et al. This project will classify the price range of the. But he is not so good at Machine Learning. We will be using supervised learning methods such as Decision Trees (DTs) , Random Forest , and Support Vector Machine (SVM) to determine the best model for this problem. 31% []. Explore and run machine learning code with Kaggle Notebooks | Using data from Samsung Mobile Price Jan 1, 2025 · Looking for a database of mobile phones specifications in Excel format to create a website, use in a GSM shop or anything similar? I started this database in August 2016, initial release had 8191 phone models, updates made it to grow to 9000 in February 2018, 10000 in January 2020, 11000 in August 2021, 12000 in January 2023, 13000 in May 2024. – Smartphones are becoming more and more important for people day by day. d. com/akshitmadan/mobile-price-classification-knnTelegram Channel- https://t. There is still a lack of study on the model of mobile phone pricing model, therefore this study investigates which features of mobile phone significantly affect its price and predict the price of mobile phone based on the Dec 26, 2020 · #datascience #model #kaggle #machinelearningCode - https://www. Classify Mobile Price Range. In the competitive mobile phone market companies want to understand sales data of mobile phones and factors which drive the prices. csv file contains a dataset that has label column used for model training, while the test. Keywords— categorization model, price range, mobile phones, dataset, battery life, RAM, internal memory, back camera, front camera, data investigation, data preprocessing, extraneous features, outliers, missing values, classification Aug 5, 2015 · In this paper, we review some advances made recently in the study of mobile phone datasets. csv. , n. This is a Python implementation of detecting mobile phones while driving using YOLO v5, performed using Kaggle's State Farm Distracted Driver Detection Dataset. In this paper, Random Forest Classifier, Logistic Regression Classifier, Decision Tree Classifier, Linear Discriminant Analysis, K-Nearest Neighbor Classifier and SVC methods are compared to predict mobile phone price class. The table Mobile Prices 2023 contains data on 1836 mobile phones, including their ratings, RAM, storage, camera specifications, battery, processor, and price in INR, with the potential to analyze trends, make comparisons, and inform purchasing decisions based on these features. built up the model depending on the multilayer perceptron topology and tested the price range of a mobile phone that was developed and trained using the dataset which shows that the ANN model can predict the mobile price range and it contains a few factors that influenced the classification of a mobile phone price range with an accuracy of 96. me/akshitmad In this kaggle challenge to goal is to determine the price range of a mobile phone. This research paper aims to implement three machine learning algorithms May 31, 2022 · Ibrahim M. The dataset was about mobile prices across different areas of the world. 2023; 13(06): 445–448. The defects are made by ourselves. Data prepared on 01. In today's market Jul 24, 2022 · With the development of technology, mobile phones are an indispensable part of human life. The chosen dataset contains 2000 instances with 21 columns of features, including 20 distinct features of mobile phones and the price range for the phone that has those features. The table contains data on 980 smartphones, including properties such as brand name, price, average rating, processor specifications, camera details, operating system, and display specifications, which can be used to analyze market trends, compare smartphone features, and make informed decisions while purchasing a smartphone. 6" Extra Bright 90Hz Display, 5000mAh, Android 14, Matte Charcoal Real-time data on phone prices, ratings, and sales trends for analysis. Nasser et al. But people fail to link those factors with the price of mobile phones; in this case, this paper is aimed to figure out the problem by using machine The dataset contains information about the used phone prices and tablets, including the model, OS, battery, screen size, storage capacity, and other relevant features. Jul 22, 2022 · Download Citation | On Jul 22, 2022, Ningyuan Hu published Classification of Mobile Phone Price Dataset Using Machine Learning Algorithms | Find, read and cite all the research you need on The dataset was initially retrieved from Kaggle under the title "Mobile Price Classification". Built using TensorFlow, this ANN model predicts mobile phone prices based on features. Our services are second to none in Myanmar online tech marketplace in Myanmar. By leveraging sales data from various companies, our aim is to identify relationships between different mobile phone features, such as RAM and internal memory, and its price range. 2023. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. And as someone who is a tech-enthusiast, reading on the rise of the mobile phone market in the past decade is unfathomable. One of those products where price matters a lot is a smartphone because it comes with a lot of features so that a company thinks a lot about how to price this mobile which can justify the features and also cover the marketing and manufacturing costs of the mobile. We’ll discuss the price range in the dataset. According to the mobile phone properties, a phone is classified into one of four price ranges ranging from zero to three. Mobile Price Range Prediction data is a data set containing information regarding RAM, Camera, Mobile Weight, Price Range of different phones. Prabhat wants to find out some relation between features of a mobile phone(eg:- RAM,Internal Memory etc) and its selling price. Data Collection The dataset of mobile prices along with different attributes was collected for the reason of variability in the prices of the mobile phones. A Django WebApp to analyze relations between specifications and prices of phones. Random forest classifier creates a set of decision trees from randomly selected I have implemented a Mobile Price Prediction using different Machine Learning Algorithms. The objective is to find out some relation between features of a mobile phone(eg:- RAM, Internal Memory, etc) and its selling price. ), specifications etc and their price range. In this paper eight classifiers including SVC, KNN, ANN, RF, Decision Tree, Naive Bayes, Linear Discriminant Analysis, Logistic Regression models are applied with different Buy & download Mobile App Data datasets instantly. Ratings — This Feature Denotes Number of the ratings gave by Explore and run machine learning code with Kaggle Notebooks | Using data from Mobile Price Classification mobile phone. I. This area of research has emerged a decade ago, with the increasing availability of large-scale anonymized datasets, and has grown into a stand-alone topic. Nov 1, 2021 · The developed model is then used to predict the price range of the new mobile phone. The accuracy scores achieved by the models are as follows: Random Forest Regression: 96. With the development of technology, mobile phones are an indispensable part of human life. The dataset is split 75/25 for training/testing, trained for 100 epochs with a batch size of 32, and the weights are saved for future use. Xiaomi all android smartphones prices, specs, reviews and showrooms in BD Nothing Phones . For this one, we have used a dataset from the Kaggle that contains phone prices and features. Mar 24, 2018 · To predict mobile phone class price, Asim et al. Model will predict the price range indicating how high the price is. This data can be used for comparative analysis, identifying trends in pricing based on specifications, and assessing market offerings by different brands. Among the older age groups, 86% of those aged 55-64 owned a smartphone device compared Shop Any Mobile Online at Jumia Egypt The Biggest Mobile Shop in Egypt - Enjoy Buying a New Mobile Phone Online in Egypt - Free Return - Secure Payment - Shop Now! Apr 28, 2021 · Smart phone price index, monthly Frequency: Monthly Table: 18-10-0209-01 (formerly CANSIM 331-0014) Mobile phone screen surface defect segmentation dataset. Overview : Develop a Classification Model for determining price range based on features available The dataset for train and test contains Built a Multi-Class classification model to find the relation between features of a mobile phone(RAM, Internal Memory etc) and its selling price. updated on Today (27/01/2025) Buy Smartphones from all the top brands like Apple, Samsung, Huawei, Google, Vivo & and more at ICT. Mobile Phones; Smart Watches; Tablets; Mobile Phone Accessories Price Rs 500 - Rs 2,000 (6) Rs 2,000 - Rs 4,000 (2) This is a complete data science project which captures and analyzes the Mobile Dataset, performes Exploratory Data Analysis on different features of the dataset and then finally trains an ML model for predicting price based on the provided features for a mobile phone. Ningyuan Hu; Read more. Learn more Jul 22, 2020 · Overview of the Dataset. Our Mobile Phone Image Dataset comprises over 3000 original images of mobile phones sourced from diverse urban and rural areas, spanning more than 1000 locations. Classification of Mobile Phone Price Dataset using Machine Learning. Within a short timespan new version with new features are launched to market (Balakumar et al. The 20 input features characterizes the phones spec and are used to train a classification model to predict the price range. Alcatel Mobiles . Feb 28, 2023 · This paper aims to explore the performance and effectiveness of feature reduction methods that accompany the Multilayer Perceptron classifier in predicting the mobile phone price range. Microprocessor clock speed. Each image has been carefully reviewed and verified by expert computer vision professionals at DC Labs, guaranteeing its accuracy and relevance. All these features play a role in determining the mobile phone’s price range. Short description of the dataset: The objective of this study is to build a model that can accurately classify a cellphone into a certain price range and determine its class. The Battery_power - Total energy a battery can store in one time measured in mAh; Blue - Has bluetooth or not; Clock_speed - speed at which microprocessor executes instructions The dataset provides a structured overview of various smartphones available in the market, capturing crucial technical specifications and pricing information. Dec 6, 2021 · In this tutorial, I have implemented a Mobile Price Prediction using different Machine Learning Algorithms. Prediction of mobile phones into different price ranges based on their features poses a significant challenge, which can be addressed through the utilization of machine learning algorithms. But people fail to link those factors with the price of mobile phones; in this case, this paper is aimed to figure out the problem by using machine This is a very detailed database with data about the world cell phone models, brands, and tech specs. Leveraging the power of data mining and extensive data analysis, we delve into a comprehensive exploration of the mobile prices dataset. Sep 11, 2024 · This research investigates upon the prediction of mobile phone prices based on various factors through the applications of multiple machine learning algorithms. Oct 27, 2022 · Classification of Mobile Phone Price Dataset Using Machine Learning Algorithms. We have performed an analysis with 25 algorithms using twenty different attributes that are effective on phone prices. INTRODUCTION The most crucial aspect of any product's marketing is its price, which is frequently what convinces a customer to buy it. The dataset provided for this project contains information about technical characteristics of mobile phones as well as price ranges. In this competitive mobile phone market you cannot simply assume things. The mobile phone industry is experiencing continuous growth, offering a wide range of mobile devices with varying features and prices. However, determining the right price for a used phone can still be a challenge. To solve this problem he collects sales data of mobile phones of various companies. This project aims to develop a machine learning model that categorizes mobile phones into different price ranges based on their features, enabling consumers to make informed decisions. com Aug 1, 2023 · 3. To build a machine learning model, we first perform EDA with various plots for better visualization. The Application of Machine Learning Algorithms to a Dataset of Mobile Phone Prices for Classification. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: ;sales@datacluster. Machine learning provides the best techniques for artificial intelligence, such as classification and regression, and can be used to build a model that accurately predicts the price range of a mobile phone. used Naive Bayes Classifier to predict and analyzed the contribution of each attribute [3]. Dec 9, 2022 · Mobile Price Dataset. The implemented regression models have been evaluated using the dataset to estimate the price of mobile phones. Leveraging linear regression, decision tree regressor, random forest regressor, gradient boosting regressor, voting regressor and support vector regressor. The goal is to perform exploratory data analysis (EDA) and create insightful visualizations to better understand trends and patterns in the data. The dataset contains various details about mobile phone hardware, specifications, and prices, which are crucial for understanding the factors that influence mobile phone pricing. The cost is Scraped data for over 1000 mobile phones, including product names, prices, descriptions, and ratings. We will use the Mobile Price dataset to classify the price range into different categories mentioned below. dollars in 2023. 2022; 7(2): 4591–4597. dollars in 2011. - amineHY/Kaggle-Mobile-Price-Classification This data science project aimed to predict mobile phone price ranges based on their specifications using machine learning algorithms. Now I have trained a mobile price classification using 3 ML algorithms. Jan 1, 2020 · The dataset includes a variety of attributes that detail mobile phone specifications. But people fail to link those factors with the price of mobile phones; in this case, this paper is aimed to figure out the problem by using machine learning algorithms like Support Vector Machine, Decision Tree, K Nearest Neighbors and Naive Bayes to train the mobile phone dataset before making predictions of the price level. Processed raw data to handle missing values,enhancing data quality and usability using Pandas. A price prediction study is conducted on different machine learning algorithms using a dataset of phone prices and features from Kaggle, 4 different models with 20 features are tackled and the highest value is obtained from Support Vector Machine with an accuracy value of 0. Jan 2, 2021 · Dataset of full list of mobile phone brands and related models from gsmarena. 10134978) Feature selection has been playing a significant role in many machine learning applications because of its omnipresent nature in any problem related to ML & DL. (AI-generated) MOTOROLA g24, 8GB+8GB RAM, 128GB ROM, MTK Helio G85, 6. This data can be used to analyze trends in the mobile phone market, compare different models, and make informed purchasing decisions. There are many companies and many types of quality products in the market. Breakdown of mobile He does not know how to estimate price of mobiles his company creates. It can be used to analyze and compare different smartphones for factors such as performance, camera quality, battery capacity, and display specifications. Every year, thousands Jul 24, 2022 · With the development of technology, mobile phones are an indispensable part of human life. Access the phones dataset for insights on mobile brands, models, and prices. csv table contains information on 984 mobile phones, including their product names, prices, ratings, reviews, and specifications. July 2022 [] Ningyuan Hu; Read more. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. As we know it, companies like Apple and Samsung lead the way in terms of hardware. Split data, apply logistic regression, KNN, SVM (linear and rbf), and evaluate using confusion matrices. Using python and simple analysis, do the following steps the main task is to train classification models to predict mobile phone prices ( ' price range' in the dataset ) and evaluate There are 3 files used in this project, train. Sep 13, 2022 · With the development of technology, mobile phones are an indispensable part of human life. This project aims to create an accurate classifier based around predicting mobile phone prices for a hypothetical phone retailer business that wants to compete with larger firms such as Samsung, Apple, etc. In this project, I visualized the training dataset in Tableau to generate insights and find out if there are any missing values, as well as obtained summary statistics and built a multinomial logistic regression model in RStudio to predict a price range of mobile phones for the stakeholder’s mobile company. The availability of the data in good volume with similarity in terms of This project revolves around assisting Bob, an entrepreneur entering the mobile phone industry, in estimating the prices of mobile phones his company produces. The dataset consists of 161 rows and 14 columns, Mobile phone prices are also the focus of attention of the mobile phone market, manufacturers and consumers. The dataset is also publicly available on Kaggle. 94% Mar 15, 2023 · In this article, I use the updated dataset containing prices of mobile (cell) phones taken from the Flipkart. 69,998 : Xiaomi Redmi Note 14 Pro+ 5G: Rs. A link to the dataset is provided, and it is also provided into the repository. Abstract: In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the price range of a mobile phone. The data features are as follows: Battery Power in mAh. In this instance, we are interested in predicting a price range rather than a particular The Mobiles_Dataset. 700M Professionals 170M Verified Profiles with Emails & Phone | Best Price Guaranteed. Browse Sub-Category . Tecno Mobiles Mobiles Price List; Mobiles: Price: 1: Samsung Galaxy S25 Ultra 12GB 1TB - Titanium Gray Aug 8, 2024 · Average selling price of smartphones in India from 2010 to 2023 (in U. Aug 1, 2023 · We used a dataset that contains mobile phones information, and there was a number of factors that influence the classification of mobile phone price. It consists of 1200 images and 400 images for each defects. It contains 21 attributes. Dec 1, 2023 · Classification of Mobile Phone Price Dataset Using Machine Learning Algorithms. Algorithms to a Dataset of Mobile Phone Prices for Classification Anil Kukreti Faculty, School of Computing, Graphic Era Hill University, Dehradun, Uttarakhand India 248002, Abstract: A mobile phone is now one of the most ubiquitous consumer goods. 0 (low cost) 1 (medium cost) in order to classify the price range for mobile phones. 2021 /brands contains file for each brand separately. The dataset contains 20 different Features of mobile phones which correspond to the label Price range as 0(low cost), 1(medium cost), 2(high cost) and 3(very high cost). Apr 20, 2023 · Our objective is to predict the price range of a mobile phone by building a model that takes into account various features provided in the dataset. assembled by various companies, including Samsung, The developed model is then used to predict the price range of the new mobile phone This article focuses on predicting the price range of mobile phones using twenty different attributes of a dataset that are features of various mobile phones used world-wide. The table provides information on various properties of real world smartphones, including brand, model, price, ratings, specifications, and features. The present research attempts to predict mobile phone prices based on features as described in Table 1 (b). The following datasets are available: Dataset with more than 8k cell phone models ; Dataset with more than 100 cell phone brands ; Dataset with cell phone models by brand for more than 100 brands ; The database aims to meet developer’s needs. Optimize market strategies. To address this issue, a machine learning model is developed using the data related to the key features of the mobile phone. Article. Many individuals fail to link the features of mobile phones with the price of mobile phones. 1 Dataset. Mobile Phone Price Prediction In this project, we are going to explore and analyze a dataset which contains specifications of two thousand mobile phones and try to predict optimum price ranges for a list of mobile phones in the market by applying various machine learning algorithms such as logistic regression, decision tree, random forest and k Mar 22, 2022 · The data contains information regarding mobile phone features, specifications etc and their price range. But people fail to link those factors with the price of mobile phones; in this case, this paper is aimed to figure out the problem by using machine Explore and run machine learning code with Kaggle Notebooks | Using data from Mobile Phone Price Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Free sample available! Mobile Price Range Prediction: Use sales data to build a classification model for mobile phone price ranges. kaggle. Mobile Phones Prices; OnePlus 13: Rs. Here is the Mobile Phones Price List updated on 28th January 2025. 30,999 Mobile Phones & Tablets. We survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical Classification of Mobile Price Using Machine Learning Nisha Sunariya1, Avinash Singh1, Mehtab Alam1,∗and Vibha Gaur1 1 Department of Computer Science, Acharya Narender Dev College, University of Delhi, New Delhi-110019, India business to find optimal product. Last Updated: 01 Dec 2023. Jul 24, 2022 · With the development of technology, mobile phones are an indispensable part of human life. Prices of several mobile phones from different brands. Discover the world's research. Bob wants to find out some relation between features of a mobile phone(eg:- RAM,Internal Memory etc) and its selling The dataset encompasses various features of mobile phones listed on Flipkart, including brand, price, ratings, and more. 1. Full details of the… Oct 13, 2022 · This Mobile Price Classification dataset takes into account the rising competitiveness of the mobile phone market. In this case, by using machine learning algorithms like Support Vector Machine, Decision Tree, K Nearest Neighbors, and Naïve Bayes to train the mobile phone price dataset before making predictions of the price range. ). of mobile phones is increasing day by day and the prices also vary by their different configurations. Samsung Mobiles dataset with all the necessary Attributes. com. Has BlueTooth or not. The phone has dual sim support or not A set of different models, that can be used to predict price range of a mobile phone. Utilized BeautifulSoup and Requests to efficiently gather data, ensuring a comprehensive dataset for analysis. Factors as battery power, CPU clock speed, has Dec 22, 2022 · We will use the Mobile Price dataset to classify the price range into different categories mentioned below. It includes features such as brand name, user ratings, RAM, ROM, mobile size, primary and selfie camera resolutions, battery power, and price. The Prediction of Mobile Phone Price Class using The Mobile Price Class dataset sourced from the Kaggle data science community website (https://www. In this question, you will work on a new dataset named 'Mobile Price Data', it contains numerous details about mobile phone hardware, specifications, and prices. price of refurbished mobile phones, such as: brand, model, technical specifications, and the states of the mobile phone. This dataset contains 3 types of surface defects: Oil, Scratch and Stain. The images are collected by industrial camera and the resolution is 1920×1080. Contribute to DaksCodes/Mobile-Phone-Price-Prediction development by creating an account on GitHub. Features include battery power, camera, memory, and connectivity. The attributes are the details of mobile phones like battery power, internal memory, ram capacity, price range, and all. To predict the accuracy of the mobile price range. Feature selection has been playing a significant role in many machine learning applications because of its omnipresent nature in any problem related to ML & DL. com website. zhznz azfvd qhanu vwn kpreryd cblpkma ysvpk phy nxtqal nnb