House price prediction using Artificial Neural Network (ANN) with adagrad optimizer
| dc.contributor.advisor | Ibrahim, Abdullahi Abdu | |
| dc.contributor.author | Abdulwahid, Ehab Saad | |
| dc.date.accessioned | 2024-09-11T07:57:16Z | |
| dc.date.available | 2024-09-11T07:57:16Z | |
| dc.date.issued | 2024 | en_US |
| dc.date.submitted | 2024 | |
| dc.department | Enstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalı | en_US |
| dc.description.abstract | The real estate market is a dynamic and complex ecosystem influenced by a myriad of factors, making accurate price predictions a formidable challenge. Understanding the intricate relationships between variables such as location, property characteristics, economic indicators, and market trends is essential for making informed investment decisions, in this thesis, a comprehensive exploration of machine learning and artificial neural networks (ANNs) has been undertaken, laying the groundwork for understanding how these powerful computational tools can be harnessed to solve complex problems across various domains. The study began by delving into the fundamentals of machine learning, categorizing it into its primary types, and discussing its applications in clustering, dimensionality reduction, and learning association rules. These sections highlighted the versatility and breadth of machine learning techniques in uncovering patterns and simplifying the complexities inherent in vast datasets. Further, a transition was made into a focused discussion on linear regression, including its simplest form and the more sophisticated gradient boosting method. This progression underscored the evolution of machine learning from basic predictive modelling to more advanced, iterative improvement techniques capable of handling nonlinear relationships with exceptional accuracy and efficiency. | en_US |
| dc.identifier.citation | Abdulwahid, E. S. (2024). House price prediction using Artificial Neural Network (ANN) with adagrad optimizer. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul. | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12939/4904 | |
| dc.identifier.yoktezid | 877180 | |
| dc.institutionauthor | Abdulwahid, Ehab Saad | |
| dc.language.iso | en | |
| dc.publisher | Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü | en_US |
| dc.relation.publicationcategory | Tez | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | ANN | en_US |
| dc.subject | AdaGrad | en_US |
| dc.subject | Housing Price Prediction | en_US |
| dc.subject | ML | en_US |
| dc.subject | AI | en_US |
| dc.title | House price prediction using Artificial Neural Network (ANN) with adagrad optimizer | |
| dc.type | Master Thesis |
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