Statistical inference and machine learning in big data
| dc.contributor.author | Temirali A. | |
| dc.date.accessioned | 2025-06-09T06:15:33Z | |
| dc.date.available | 2025-06-09T06:15:33Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | In my practice. I met with different definitions: - Big Data is when data is more than 100GB (500GB. 1TB. who likes it) - Big Data is data that cannot be processed in Excel - Big Data is data that cannot be processed on a single computer. And even such: - Big Data is generally any data. - Big Data does not exist. marketers have invented it. Thus, under Big Data I will understand not some specific amount of data or even the data itself, but their processing methods. which allow distributed information to be processed. These methods cat? be applied both to huge data arrays (such as the content of all pages on the Internet) and to small ones (such as the content of this thesis). | |
| dc.identifier.citation | Temirali A / Statistical inference and machine learning in big data / Faculty of Engineering and Natural Science / 6M060100 - 2019 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1744 | |
| dc.language.iso | en | |
| dc.publisher | Faculty of Engineering and Natural Science | |
| dc.subject | machine learning | |
| dc.subject | big data | |
| dc.subject | methods | |
| dc.subject | Statistical Inference | |
| dc.title | Statistical inference and machine learning in big data | |
| dc.type | Thesis |