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This repository offers a complete project on predicting used car prices using machine learning. It features data cleaning, model selection, training, and evaluation in a Jupyter Notebook, along with a Streamlit app for interactive predictions.
23 Νοε 2020 · Essentially, the company wants to know: Which variables are significant in predicting the price of a car. How well those variables describe the price of a car. Based on various market surveys, the consulting firm has gathered a large dataset of different types of cars across the American market.
11 Αυγ 2020 · A Machine Learning Project that uses Random Forest Regressor model to predict used cars price based on some attributes such as kilometers driven, age, number of previous owners etc.
The Car Price Prediction is a flask web application which predicts car prices based on given independent features like Car_Name, Year, Selling_Price, Present_Price, Kms_Driven, Fuel_Type, Seller_Type, Transmission, and Owner.
4 Αυγ 2021 · Car Price Prediction Model using Python. The dataset I’m using here to train a car price prediction model was downloaded from Kaggle. It contains data about all the main features that contribute to the price of a car. So let’s start this task by importing the necessary Python libraries and the dataset:
22 Μαρ 2021 · How to Build Your First Predictive Model Using Linear Regression If you’ve ever wondered how people predict house prices, stock movements, or even the weather using math and code, you’ve ...
25 Ιουλ 2023 · As a Data Scientist, you are given the task of creating an automated system that predicts the selling price of cars based on various features (information) such as the car’s model name,...
