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Car Price Prediction Using Machine Learning

Ashish Chandak1 , Prajwal Ganorkar2 , Shyam Sharma3 , Ayushi Bagmar4 , Soumya Tiwari5

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-5 , Page no. 444-450, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i5.444450

Online published on May 31, 2019

Copyright © Ashish Chandak, Prajwal Ganorkar, Shyam Sharma, Ayushi Bagmar, Soumya Tiwari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Ashish Chandak, Prajwal Ganorkar, Shyam Sharma, Ayushi Bagmar, Soumya Tiwari, “Car Price Prediction Using Machine Learning,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.444-450, 2019.

MLA Style Citation: Ashish Chandak, Prajwal Ganorkar, Shyam Sharma, Ayushi Bagmar, Soumya Tiwari "Car Price Prediction Using Machine Learning." International Journal of Computer Sciences and Engineering 7.5 (2019): 444-450.

APA Style Citation: Ashish Chandak, Prajwal Ganorkar, Shyam Sharma, Ayushi Bagmar, Soumya Tiwari, (2019). Car Price Prediction Using Machine Learning. International Journal of Computer Sciences and Engineering, 7(5), 444-450.

BibTex Style Citation:
@article{Chandak_2019,
author = {Ashish Chandak, Prajwal Ganorkar, Shyam Sharma, Ayushi Bagmar, Soumya Tiwari},
title = {Car Price Prediction Using Machine Learning},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {444-450},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4262},
doi = {https://doi.org/10.26438/ijcse/v7i5.444450}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.444450}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4262
TI - Car Price Prediction Using Machine Learning
T2 - International Journal of Computer Sciences and Engineering
AU - Ashish Chandak, Prajwal Ganorkar, Shyam Sharma, Ayushi Bagmar, Soumya Tiwari
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 444-450
IS - 5
VL - 7
SN - 2347-2693
ER -

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Abstract

Because of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It’s a science that’s not new – but one that has gained fresh momentum. While there is an end number of applications of machine learning in real life one of the most prominent application is the prediction problems. There are various topics on which the prediction can be applied. One such application is what this project is focused upon. Websites recommending items you might like based on previous purchases are using machine learning to analyze your buying history – and promote other items you`d be interested in. This ability to capture data, analyze it and use it to personalize a shopping experience (or implement a marketing campaign) is the future of retail

Key-Words / Index Term

Environment Quality, Data Analysis, Business Intelligence, Power BI, SQL Server 2016, Air Quality, Water Quality, Tree Cover, Forest Cover, Predictions, NLP, forecasting, k-means clustering, ARIMA

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