House Price Prediction Using Machine Learning and Artificial Intelligence

Authors

  • Fatbardha Maloku Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA Author
  • Besnik Maloku Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA Author
  • Akansha Agarwal Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA Author
  • Dinesh Kumar Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA Author

DOI:

https://doi.org/10.47363/JAICC/2024(3)357

Keywords:

businesses, real estate, investment, forecast

Abstract

The escalating annual rise in housing prices introduces volatility and uncertainty into the real estate market, underscoring the critical need for accurate price forecasting systems. Predicting house prices accurately remains challenging due to the multitude of influencing factors. This study aims to identify and analyze key determinants affecting house prices, employing two established machine learning models. Through comparative analysis, the research will recommend the most effective model for enhancing the accuracy of house price predictions.

Author Biographies

  • Fatbardha Maloku, Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA

    Fatbardha Maloku, Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California
    94105, USA.

  • Besnik Maloku, Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA

    Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA

  • Akansha Agarwal , Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA

    Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA

  • Dinesh Kumar, Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA

    Master of Science in Business Analytics Student Candidates, Ageno School of Business, Golden Gate University, San Francisco, California 94105, USA

Downloads

Published

2024-08-12

Issue

Vol. 3 No. 4 (2024): Volume 3 Issue 4

Section

Articles

License

Copyright (c) 2025 Journal of Artificial Intelligence & Cloud Computing

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

House Price Prediction Using Machine Learning and Artificial Intelligence. (2024). Journal of Artificial Intelligence & Cloud Computing, 3(4), 1-10. https://doi.org/10.47363/JAICC/2024(3)357

Similar Articles

11-20 of 189

You may also start an advanced similarity search for this article.