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DC Field | Value | Language |
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dc.contributor.author | Ashwini Doke | - |
dc.date.accessioned | 2022-10-14T14:05:00Z | - |
dc.date.available | 2022-10-14T14:05:00Z | - |
dc.date.issued | 2021-06 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/6649 | - |
dc.description.abstract | Automated Machine Learning is an area ofresearch that has gainedlots ofresearch in the past few years. To build a high qualityrnodel for Machine learning we need technical experts who have good knowledge in exploring various machines learning algoritlun as well as to tune the hyperpararneters efficiently. The size ofdata is increasing, it is observed that data scientist cannot address this challenging tasks due to lack ofexpertise and experience in the respective domain. So, there is a need to automate such crucial task inthe domain ofmachine learning. Metaleaming is "learning to learn" like human expertise. This paper is initial survey of ongoing research in field of Meta Learning and AutoML | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | IEEE Xplore | en_US |
dc.subject | Computer Science / Information Science | en_US |
dc.title | Survey on Automated Machine Learning (AutoML) and Meta learning | en_US |
dc.title.alternative | Computer Science / Information Science | en_US |
dc.type | Working Paper | en_US |
Appears in Collections: | 2021 |
Files in This Item:
File | Description | Size | Format | |
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5. PAPER5ISE.pdf | 671.23 kB | Adobe PDF | View/Open |
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