Αποτελέσματα Αναζήτησης
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.
10 Μαΐ 2022 · Using features such as MPG, model, year of manufacture and engine type, predict the price of cars with machine learning and data science.
els to predict the price of a product given its image, and vi-sualize the features that result in higher or lower price pre-dictions. We collect two novel datasets of product images and their MSRP prices for this purpose: a bicycle dataset and a car dataset. We set baselines for price regression using linear regression on histogram of oriented ...
14 Οκτ 2020 · With this project, we have built a model that can predict with a 87,03% of accuracy the price of used cars, given a set of features. This information can have an enormous value for both companies and individuals when trying to understand how to estimate the value of a vehicle and, more importantly, the key factors that determine its pricing.
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:
P90X gives you intense cross-training with 5 hard-core resistance routines, 3 fat-scorching cardio routines, and 2 ab-ripping routines, as well as extreme yoga and advanced flexibility.
