Hyperparameter Tuning for Machine and Deep Learning with R
Springer Nature Singapore
Title |
Hyperparameter Tuning for Machine and Deep Learning with R
|
---|---|
Published by |
Springer Nature Singapore, January 2023
|
DOI | 10.1007/978-981-19-5170-1 |
ISBNs |
978-9-81-195169-5, 978-9-81-195170-1
|
Editors |
Bartz, Eva, Bartz-Beielstein, Thomas, Zaefferer, Martin, Mersmann, Olaf |
Country | Count | As % |
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Germany | 3 | 17% |
Ecuador | 1 | 6% |
Brazil | 1 | 6% |
United Kingdom | 1 | 6% |
United States | 1 | 6% |
Unknown | 11 | 61% |
Type | Count | As % |
---|---|---|
Members of the public | 14 | 78% |
Scientists | 3 | 17% |
Science communicators (journalists, bloggers, editors) | 1 | 6% |
Country | Count | As % |
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Unknown | 139 | 100% |
Readers by professional status | Count | As % |
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Student > Master | 13 | 9% |
Student > Bachelor | 10 | 7% |
Lecturer | 6 | 4% |
Other | 3 | 2% |
Student > Ph. D. Student | 3 | 2% |
Other | 17 | 12% |
Unknown | 87 | 63% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 15 | 11% |
Engineering | 13 | 9% |
Agricultural and Biological Sciences | 4 | 3% |
Biochemistry, Genetics and Molecular Biology | 3 | 2% |
Social Sciences | 2 | 1% |
Other | 13 | 9% |
Unknown | 89 | 64% |