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dc.contributor.authorMiroslaw Staron Tác giả: Staron, Miroslaw-
dc.date.accessioned2024-11-19T08:50:15Z-
dc.date.available2024-11-19T08:50:15Z-
dc.date.issued2024-
dc.identifier.urihttp://thuvienso.thanglong.edu.vn//handle/TLU/11749-
dc.description.abstractThe book begins by introducing the main concepts of professional software systems that leverage machine learning at their core. As you progress, you'll explore the differences between traditional, non-ML software, and machine learning software. The initial best practices will guide you in determining the type of software you need for your product. Subsequently, you will delve into algorithms, covering their selection, development, and testing before exploring the intricacies of the infrastructure for machine learning systems by defining best practices for identifying the right data source and ensuring its quality.vi
dc.language.isoenvi
dc.subjectMachine learning | Software systems | Thuật toán | Hệ thống phần mềmvi
dc.titleMachine Learning Infrastructure and Best Practices for Software Engineers : Take Your Machine Learning Software from a Prototype to a Fully Fledged Software Systemvi
dc.typeSách/Bookvi
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