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http://localhost:8080/xmlui/handle/123456789/3888
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Athavani, Shahin | - |
dc.contributor.author | Shaikh, Meraj Muzammil(18ET40) | - |
dc.contributor.author | Shaikh, Rahmat Ali(16ET25) | - |
dc.contributor.author | Ansari, Raisuddin(19DET05) | - |
dc.contributor.author | Khan, Adil(17ET21) | - |
dc.date.accessioned | 2022-06-17T10:36:39Z | - |
dc.date.available | 2022-06-17T10:36:39Z | - |
dc.date.issued | 2022-05 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/3888 | - |
dc.description.abstract | Machine learning plays a major role from past years in image detection, spam reorganization, normal speech command, product recommendation and medical diagnosis. Present machine learning algorithm helps us in enhancing security alerts, ensuring public safety and improve medical enhancements. Machine learning system also provides better customer service and safer automobile systems. We create a housing cost prediction model in view of machine learning algorithm models for example, XGBoost, Linear regression and neural system on look at their order precision execution. We in that point recommend a housing cost prediction model to support a house vender or a real estate agent for better information based on the valuation of house. Those examinations exhibit that Linear regression algorithm, in view of accuracy, reliably outperforms alternate models in the execution of housing cost prediction. | en_US |
dc.language.iso | en | en_US |
dc.publisher | AIKTC | en_US |
dc.subject | Project Report - EXTC | en_US |
dc.title | House price prediction | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | EXTC Engineering - Project Reports |
Files in This Item:
File | Description | Size | Format | |
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18ET40.pdf Until 2025-06-30 | Black Book | 1.38 MB | Adobe PDF | View/Open Request a copy |
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