Generate synthetic datasets and scenarios by learning from the real world
The modern paradigms of machine learning algorithms and artificial intelligence base their success on processing a large quantity of data. Nevertheless, data does not come for free, and it can sometimes be practically unfeasible to collect enough data to train machine learning models successfully. T...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-305275 |