| Judul | Software Engineering and Data Science / Davide Tosi (editor) |
| Pengarang | Tosi, Davide |
| Penerbitan | Basel : MDPI - Multidisciplinary Digital Publishing Institute, 2023 |
| Deskripsi Fisik | 132 p. :ill. |
| ISBN | 9783036564401, 9783036564418 |
| Subjek | INFORMATION TECHNOLOGY INDUSTRIES DATA SCIENCE |
| Catatan | This reprint focuses on data-driven software solutions and their impact on research and development at the academic, industry, business, and government levels to exploit the hidden knowledge and big data that can be offered to cities and citizens in the future. Data-driven software solutions are different from “traditional” software development projects, as the focus of the main development core is on managing the data (e.g., data store and data quality) and designing behavioral models with the aid of artificial intelligence and machine learning techniques. To this end, new life cycles, algorithms, methods, processes, and tools are required. This reprint is centered on the recent trends and advancements in the field of engineering data-intensive software solutions to address the challenges in developing, testing, and maintaining such data-driven systems, with a focus on the application of data-driven solutions to real-life problems and techniques and algorithms addressing the different challenges of data-driv |
| Bentuk Karya | Tidak ada kode yang sesuai |
| Target Pembaca | Tidak ada kode yang sesuai |
| Lokasi Akses Online |
https://directory.doabooks.org/handle/20.500.12854/96748 https://oer.unair.ac.id/files/original/24070ee6a4767be77b9970313dd83eef.pdf |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 299225192 | 001.642 Sof | Baca Online | Perpustakaan Pusat - Online Resources Ebook |
Tersedia |
| Tag | Ind1 | Ind2 | Isi |
| 001 | INLIS000000000159301 | ||
| 005 | 20250317114012 | ||
| 007 | ta | ||
| 008 | 250317################|##########|#|## | ||
| 020 | # | # | $a 9783036564401, 9783036564418 |
| 035 | # | # | $a 0010-0325000920 |
| 082 | # | # | $a 001.642 |
| 084 | # | # | $a 001.642 Sof |
| 245 | # | # | $a Software Engineering and Data Science /$c Davide Tosi (editor) |
| 260 | # | # | $a Basel :$b MDPI - Multidisciplinary Digital Publishing Institute,$c 2023 |
| 300 | # | # | $a 132 p. : $b ill. |
| 505 | # | # | $a This reprint focuses on data-driven software solutions and their impact on research and development at the academic, industry, business, and government levels to exploit the hidden knowledge and big data that can be offered to cities and citizens in the future. Data-driven software solutions are different from “traditional” software development projects, as the focus of the main development core is on managing the data (e.g., data store and data quality) and designing behavioral models with the aid of artificial intelligence and machine learning techniques. To this end, new life cycles, algorithms, methods, processes, and tools are required. This reprint is centered on the recent trends and advancements in the field of engineering data-intensive software solutions to address the challenges in developing, testing, and maintaining such data-driven systems, with a focus on the application of data-driven solutions to real-life problems and techniques and algorithms addressing the different challenges of data-driven software engineering. |
| 650 | # | # | $a DATA SCIENCE |
| 650 | # | # | $a INFORMATION TECHNOLOGY INDUSTRIES |
| 700 | 1 | # | $a Tosi, Davide |
| 856 | # | # | $a https://directory.doabooks.org/handle/20.500.12854/96748 |
| 856 | # | # | $a https://oer.unair.ac.id/files/original/24070ee6a4767be77b9970313dd83eef.pdf |
| 990 | # | # | $a 299225192 |
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