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

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Published

2024-08-12

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

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